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<li class="navelem"><a class="el" href="dir_6b3ae6988449b0834e9596fad5d75199.html">gpu</a></li><li class="navelem"><a class="el" href="dir_498271007b03b2a0521055e88776887b.html">utils</a></li>  </ul>
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<div class="title">Tensor-inl.cuh</div>  </div>
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<div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno">    1</span>&#160;<span class="comment">/**</span></div>
<div class="line"><a name="l00002"></a><span class="lineno">    2</span>&#160;<span class="comment"> * Copyright (c) 2015-present, Facebook, Inc.</span></div>
<div class="line"><a name="l00003"></a><span class="lineno">    3</span>&#160;<span class="comment"> * All rights reserved.</span></div>
<div class="line"><a name="l00004"></a><span class="lineno">    4</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00005"></a><span class="lineno">    5</span>&#160;<span class="comment"> * This source code is licensed under the BSD+Patents license found in the</span></div>
<div class="line"><a name="l00006"></a><span class="lineno">    6</span>&#160;<span class="comment"> * LICENSE file in the root directory of this source tree.</span></div>
<div class="line"><a name="l00007"></a><span class="lineno">    7</span>&#160;<span class="comment"> */</span></div>
<div class="line"><a name="l00008"></a><span class="lineno">    8</span>&#160;</div>
<div class="line"><a name="l00009"></a><span class="lineno">    9</span>&#160;<span class="comment">// Copyright 2004-present Facebook. All Rights Reserved.</span></div>
<div class="line"><a name="l00010"></a><span class="lineno">   10</span>&#160;</div>
<div class="line"><a name="l00011"></a><span class="lineno">   11</span>&#160;<span class="preprocessor">#include &quot;../GpuFaissAssert.h&quot;</span></div>
<div class="line"><a name="l00012"></a><span class="lineno">   12</span>&#160;<span class="preprocessor">#include &quot;DeviceUtils.h&quot;</span></div>
<div class="line"><a name="l00013"></a><span class="lineno">   13</span>&#160;<span class="preprocessor">#include &lt;limits&gt;</span></div>
<div class="line"><a name="l00014"></a><span class="lineno">   14</span>&#160;</div>
<div class="line"><a name="l00015"></a><span class="lineno">   15</span>&#160;<span class="keyword">namespace </span>faiss { <span class="keyword">namespace </span>gpu {</div>
<div class="line"><a name="l00016"></a><span class="lineno">   16</span>&#160;</div>
<div class="line"><a name="l00017"></a><span class="lineno">   17</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T, <span class="keywordtype">int</span> Dim, <span class="keywordtype">bool</span> InnerContig,</div>
<div class="line"><a name="l00018"></a><span class="lineno">   18</span>&#160;          <span class="keyword">typename</span> IndexT, <span class="keyword">template</span> &lt;<span class="keyword">typename</span> U&gt; <span class="keyword">class </span>PtrTraits&gt;</div>
<div class="line"><a name="l00019"></a><span class="lineno">   19</span>&#160;__host__ __device__</div>
<div class="line"><a name="l00020"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1Tensor.html#a8ae7b3f95991125a5648c3b78afd40bd">   20</a></span>&#160;<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a8ae7b3f95991125a5648c3b78afd40bd">Tensor&lt;T, Dim, InnerContig, IndexT, PtrTraits&gt;::Tensor</a>()</div>
<div class="line"><a name="l00021"></a><span class="lineno">   21</span>&#160;    : data_(nullptr) {</div>
<div class="line"><a name="l00022"></a><span class="lineno">   22</span>&#160;  static_assert(Dim &gt; 0, <span class="stringliteral">&quot;must have &gt; 0 dimensions&quot;</span>);</div>
<div class="line"><a name="l00023"></a><span class="lineno">   23</span>&#160;</div>
<div class="line"><a name="l00024"></a><span class="lineno">   24</span>&#160;  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; Dim; ++i) {</div>
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<div class="line"><a name="l00026"></a><span class="lineno">   26</span>&#160;    <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#af4b8fe4b632cdca51ee7972ed93fc3fa">stride_</a>[i] = (IndexT) 1;</div>
<div class="line"><a name="l00027"></a><span class="lineno">   27</span>&#160;  }</div>
<div class="line"><a name="l00028"></a><span class="lineno">   28</span>&#160;}</div>
<div class="line"><a name="l00029"></a><span class="lineno">   29</span>&#160;</div>
<div class="line"><a name="l00030"></a><span class="lineno">   30</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T, <span class="keywordtype">int</span> Dim, <span class="keywordtype">bool</span> InnerContig,</div>
<div class="line"><a name="l00031"></a><span class="lineno">   31</span>&#160;          <span class="keyword">typename</span> IndexT, <span class="keyword">template</span> &lt;<span class="keyword">typename</span> U&gt; <span class="keyword">class </span>PtrTraits&gt;</div>
<div class="line"><a name="l00032"></a><span class="lineno">   32</span>&#160;__host__ __device__</div>
<div class="line"><a name="l00033"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1Tensor.html#a4396d8789bb829a4d614900b2a632bc9">   33</a></span>&#160;<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a8ae7b3f95991125a5648c3b78afd40bd">Tensor&lt;T, Dim, InnerContig, IndexT, PtrTraits&gt;::Tensor</a>(</div>
<div class="line"><a name="l00034"></a><span class="lineno">   34</span>&#160;  <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor&lt;T, Dim, InnerContig, IndexT, PtrTraits&gt;</a>&amp; t) {</div>
<div class="line"><a name="l00035"></a><span class="lineno">   35</span>&#160;  this-&gt;operator=(t);</div>
<div class="line"><a name="l00036"></a><span class="lineno">   36</span>&#160;}</div>
<div class="line"><a name="l00037"></a><span class="lineno">   37</span>&#160;</div>
<div class="line"><a name="l00038"></a><span class="lineno">   38</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T, <span class="keywordtype">int</span> Dim, <span class="keywordtype">bool</span> InnerContig,</div>
<div class="line"><a name="l00039"></a><span class="lineno">   39</span>&#160;          <span class="keyword">typename</span> IndexT, <span class="keyword">template</span> &lt;<span class="keyword">typename</span> U&gt; <span class="keyword">class </span>PtrTraits&gt;</div>
<div class="line"><a name="l00040"></a><span class="lineno">   40</span>&#160;__host__ __device__</div>
<div class="line"><a name="l00041"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1Tensor.html#a37db8663b2fd9e1da8c4dea4e2bdb1f3">   41</a></span>&#160;<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a8ae7b3f95991125a5648c3b78afd40bd">Tensor&lt;T, Dim, InnerContig, IndexT, PtrTraits&gt;::Tensor</a>(</div>
<div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160;  <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor&lt;T, Dim, InnerContig, IndexT, PtrTraits&gt;</a>&amp;&amp; t) {</div>
<div class="line"><a name="l00043"></a><span class="lineno">   43</span>&#160;  this-&gt;operator=(std::move(t));</div>
<div class="line"><a name="l00044"></a><span class="lineno">   44</span>&#160;}</div>
<div class="line"><a name="l00045"></a><span class="lineno">   45</span>&#160;</div>
<div class="line"><a name="l00046"></a><span class="lineno">   46</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T, <span class="keywordtype">int</span> Dim, <span class="keywordtype">bool</span> InnerContig,</div>
<div class="line"><a name="l00047"></a><span class="lineno">   47</span>&#160;          <span class="keyword">typename</span> IndexT, <span class="keyword">template</span> &lt;<span class="keyword">typename</span> U&gt; <span class="keyword">class </span>PtrTraits&gt;</div>
<div class="line"><a name="l00048"></a><span class="lineno">   48</span>&#160;__host__ __device__</div>
<div class="line"><a name="l00049"></a><span class="lineno">   49</span>&#160;<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor&lt;T, Dim, InnerContig, IndexT, PtrTraits&gt;</a>&amp;</div>
<div class="line"><a name="l00050"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1Tensor.html#a0d831a352531281e06250cc6fe52a38a">   50</a></span>&#160;<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a0d831a352531281e06250cc6fe52a38a">Tensor&lt;T, Dim, InnerContig, IndexT, PtrTraits&gt;::operator=</a>(</div>
<div class="line"><a name="l00051"></a><span class="lineno">   51</span>&#160;  <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor&lt;T, Dim, InnerContig, IndexT, PtrTraits&gt;</a>&amp; t) {</div>
<div class="line"><a name="l00052"></a><span class="lineno">   52</span>&#160;  data_ = t.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a2ec506a25e46cf7001060a6ba5ae3b94">data_</a>;</div>
<div class="line"><a name="l00053"></a><span class="lineno">   53</span>&#160;  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; Dim; ++i) {</div>
<div class="line"><a name="l00054"></a><span class="lineno">   54</span>&#160;    size_[i] = t.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#ad96fbf0f5e7c06a1031b8b18f7fc01d7">size_</a>[i];</div>
<div class="line"><a name="l00055"></a><span class="lineno">   55</span>&#160;    stride_[i] = t.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#af4b8fe4b632cdca51ee7972ed93fc3fa">stride_</a>[i];</div>
<div class="line"><a name="l00056"></a><span class="lineno">   56</span>&#160;  }</div>
<div class="line"><a name="l00057"></a><span class="lineno">   57</span>&#160;</div>
<div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160;  <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div>
<div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;}</div>
<div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;</div>
<div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T, <span class="keywordtype">int</span> Dim, <span class="keywordtype">bool</span> InnerContig,</div>
<div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160;          <span class="keyword">typename</span> IndexT, <span class="keyword">template</span> &lt;<span class="keyword">typename</span> U&gt; <span class="keyword">class </span>PtrTraits&gt;</div>
<div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;__host__ __device__</div>
<div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor&lt;T, Dim, InnerContig, IndexT, PtrTraits&gt;</a>&amp;</div>
<div class="line"><a name="l00065"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1Tensor.html#ae086a03b8067e18d0c2dda0892dc9e39">   65</a></span>&#160;<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a0d831a352531281e06250cc6fe52a38a">Tensor&lt;T, Dim, InnerContig, IndexT, PtrTraits&gt;::operator=</a>(</div>
<div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;  <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor&lt;T, Dim, InnerContig, IndexT, PtrTraits&gt;</a>&amp;&amp; t) {</div>
<div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;  data_ = t.data_; t.data_ = <span class="keyword">nullptr</span>;</div>
<div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; Dim; ++i) {</div>
<div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160;    stride_[i] = t.stride_[i]; t.stride_[i] = 0;</div>
<div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160;    size_[i] = t.size_[i]; t.size_[i] = 0;</div>
<div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;  }</div>
<div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;</div>
<div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160;  <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div>
<div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160;}</div>
<div class="line"><a name="l00075"></a><span class="lineno">   75</span>&#160;</div>
<div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T, <span class="keywordtype">int</span> Dim, <span class="keywordtype">bool</span> InnerContig,</div>
<div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160;          <span class="keyword">typename</span> IndexT, <span class="keyword">template</span> &lt;<span class="keyword">typename</span> U&gt; <span class="keyword">class </span>PtrTraits&gt;</div>
<div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;__host__ __device__</div>
<div class="line"><a name="l00079"></a><span class="lineno">   79</span>&#160;<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a8ae7b3f95991125a5648c3b78afd40bd">Tensor&lt;T, Dim, InnerContig, IndexT, PtrTraits&gt;::</a></div>
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<div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160;    : data_(data) {</div>
<div class="line"><a name="l00082"></a><span class="lineno">   82</span>&#160;  static_assert(Dim &gt; 0, <span class="stringliteral">&quot;must have &gt; 0 dimensions&quot;</span>);</div>
<div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160;</div>
<div class="line"><a name="l00084"></a><span class="lineno">   84</span>&#160;  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; Dim; ++i) {</div>
<div class="line"><a name="l00085"></a><span class="lineno">   85</span>&#160;    <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#ad96fbf0f5e7c06a1031b8b18f7fc01d7">size_</a>[i] = <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#abc0ecc4f882ee09632b5a06be0619adb">sizes</a>[i];</div>
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<div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160;  }</div>
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<div class="line"><a name="l00093"></a><span class="lineno">   93</span>&#160;</div>
<div class="line"><a name="l00094"></a><span class="lineno">   94</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T, <span class="keywordtype">int</span> Dim, <span class="keywordtype">bool</span> InnerContig,</div>
<div class="line"><a name="l00095"></a><span class="lineno">   95</span>&#160;          <span class="keyword">typename</span> IndexT, <span class="keyword">template</span> &lt;<span class="keyword">typename</span> U&gt; <span class="keyword">class </span>PtrTraits&gt;</div>
<div class="line"><a name="l00096"></a><span class="lineno">   96</span>&#160;__host__ __device__</div>
<div class="line"><a name="l00097"></a><span class="lineno">   97</span>&#160;<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a8ae7b3f95991125a5648c3b78afd40bd">Tensor&lt;T, Dim, InnerContig, IndexT, PtrTraits&gt;::</a></div>
<div class="line"><a name="l00098"></a><span class="lineno">   98</span>&#160;<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a8ae7b3f95991125a5648c3b78afd40bd">Tensor</a>(DataPtrType data, std::initializer_list&lt;IndexT&gt; sizes)</div>
<div class="line"><a name="l00099"></a><span class="lineno">   99</span>&#160;    : data_(data) {</div>
<div class="line"><a name="l00100"></a><span class="lineno">  100</span>&#160;  GPU_FAISS_ASSERT(sizes.size() == Dim);</div>
<div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160;  static_assert(Dim &gt; 0, <span class="stringliteral">&quot;must have &gt; 0 dimensions&quot;</span>);</div>
<div class="line"><a name="l00102"></a><span class="lineno">  102</span>&#160;</div>
<div class="line"><a name="l00103"></a><span class="lineno">  103</span>&#160;  <span class="keywordtype">int</span> i = 0;</div>
<div class="line"><a name="l00104"></a><span class="lineno">  104</span>&#160;  <span class="keywordflow">for</span> (<span class="keyword">auto</span> s : sizes) {</div>
<div class="line"><a name="l00105"></a><span class="lineno">  105</span>&#160;    <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#ad96fbf0f5e7c06a1031b8b18f7fc01d7">size_</a>[i++] = s;</div>
<div class="line"><a name="l00106"></a><span class="lineno">  106</span>&#160;  }</div>
<div class="line"><a name="l00107"></a><span class="lineno">  107</span>&#160;</div>
<div class="line"><a name="l00108"></a><span class="lineno">  108</span>&#160;  <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#af4b8fe4b632cdca51ee7972ed93fc3fa">stride_</a>[Dim - 1] = (IndexT) 1;</div>
<div class="line"><a name="l00109"></a><span class="lineno">  109</span>&#160;  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> j = Dim - 2; j &gt;= 0; --j) {</div>
<div class="line"><a name="l00110"></a><span class="lineno">  110</span>&#160;    <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#af4b8fe4b632cdca51ee7972ed93fc3fa">stride_</a>[j] = <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#af4b8fe4b632cdca51ee7972ed93fc3fa">stride_</a>[j + 1] * <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#ad96fbf0f5e7c06a1031b8b18f7fc01d7">size_</a>[j + 1];</div>
<div class="line"><a name="l00111"></a><span class="lineno">  111</span>&#160;  }</div>
<div class="line"><a name="l00112"></a><span class="lineno">  112</span>&#160;}</div>
<div class="line"><a name="l00113"></a><span class="lineno">  113</span>&#160;</div>
<div class="line"><a name="l00114"></a><span class="lineno">  114</span>&#160;</div>
<div class="line"><a name="l00115"></a><span class="lineno">  115</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T, <span class="keywordtype">int</span> Dim, <span class="keywordtype">bool</span> InnerContig,</div>
<div class="line"><a name="l00116"></a><span class="lineno">  116</span>&#160;          <span class="keyword">typename</span> IndexT, <span class="keyword">template</span> &lt;<span class="keyword">typename</span> U&gt; <span class="keyword">class </span>PtrTraits&gt;</div>
<div class="line"><a name="l00117"></a><span class="lineno">  117</span>&#160;__host__ __device__</div>
<div class="line"><a name="l00118"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1Tensor.html#ac651b20d86813b8928f05cde4fb1ff7d">  118</a></span>&#160;<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a8ae7b3f95991125a5648c3b78afd40bd">Tensor&lt;T, Dim, InnerContig, IndexT, PtrTraits&gt;::Tensor</a>(</div>
<div class="line"><a name="l00119"></a><span class="lineno">  119</span>&#160;  DataPtrType data, <span class="keyword">const</span> IndexT sizes[Dim], <span class="keyword">const</span> IndexT strides[Dim])</div>
<div class="line"><a name="l00120"></a><span class="lineno">  120</span>&#160;    : data_(data) {</div>
<div class="line"><a name="l00121"></a><span class="lineno">  121</span>&#160;  static_assert(Dim &gt; 0, <span class="stringliteral">&quot;must have &gt; 0 dimensions&quot;</span>);</div>
<div class="line"><a name="l00122"></a><span class="lineno">  122</span>&#160;</div>
<div class="line"><a name="l00123"></a><span class="lineno">  123</span>&#160;  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; Dim; ++i) {</div>
<div class="line"><a name="l00124"></a><span class="lineno">  124</span>&#160;    <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#ad96fbf0f5e7c06a1031b8b18f7fc01d7">size_</a>[i] = sizes[i];</div>
<div class="line"><a name="l00125"></a><span class="lineno">  125</span>&#160;    <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#af4b8fe4b632cdca51ee7972ed93fc3fa">stride_</a>[i] = <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a87a777247486756e99060547a3cc833a">strides</a>[i];</div>
<div class="line"><a name="l00126"></a><span class="lineno">  126</span>&#160;  }</div>
<div class="line"><a name="l00127"></a><span class="lineno">  127</span>&#160;}</div>
<div class="line"><a name="l00128"></a><span class="lineno">  128</span>&#160;</div>
<div class="line"><a name="l00129"></a><span class="lineno">  129</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T, <span class="keywordtype">int</span> Dim, <span class="keywordtype">bool</span> InnerContig,</div>
<div class="line"><a name="l00130"></a><span class="lineno">  130</span>&#160;          <span class="keyword">typename</span> IndexT, <span class="keyword">template</span> &lt;<span class="keyword">typename</span> U&gt; <span class="keyword">class </span>PtrTraits&gt;</div>
<div class="line"><a name="l00131"></a><span class="lineno">  131</span>&#160;__host__ <span class="keywordtype">void</span></div>
<div class="line"><a name="l00132"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1Tensor.html#a6dc00c182a92389b74c89ba7fcab40d3">  132</a></span>&#160;<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a6dc00c182a92389b74c89ba7fcab40d3">Tensor&lt;T, Dim, InnerContig, IndexT, PtrTraits&gt;::copyFrom</a>(</div>
<div class="line"><a name="l00133"></a><span class="lineno">  133</span>&#160;  <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor&lt;T, Dim, InnerContig, IndexT, PtrTraits&gt;</a>&amp; t,</div>
<div class="line"><a name="l00134"></a><span class="lineno">  134</span>&#160;  cudaStream_t stream) {</div>
<div class="line"><a name="l00135"></a><span class="lineno">  135</span>&#160;  <span class="comment">// The tensor must be fully contiguous</span></div>
<div class="line"><a name="l00136"></a><span class="lineno">  136</span>&#160;  GPU_FAISS_ASSERT(this-&gt;isContiguous());</div>
<div class="line"><a name="l00137"></a><span class="lineno">  137</span>&#160;</div>
<div class="line"><a name="l00138"></a><span class="lineno">  138</span>&#160;  <span class="comment">// Size must be the same (since dimensions are checked and</span></div>
<div class="line"><a name="l00139"></a><span class="lineno">  139</span>&#160;  <span class="comment">// continuity is assumed, we need only check total number of</span></div>
<div class="line"><a name="l00140"></a><span class="lineno">  140</span>&#160;  <span class="comment">// elements</span></div>
<div class="line"><a name="l00141"></a><span class="lineno">  141</span>&#160;  GPU_FAISS_ASSERT(this-&gt;numElements() == t.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a0ba9ab7c1676b7a41a6e6b2e5a490d2f">numElements</a>());</div>
<div class="line"><a name="l00142"></a><span class="lineno">  142</span>&#160;</div>
<div class="line"><a name="l00143"></a><span class="lineno">  143</span>&#160;  <span class="keywordflow">if</span> (t.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a0ba9ab7c1676b7a41a6e6b2e5a490d2f">numElements</a>() &gt; 0) {</div>
<div class="line"><a name="l00144"></a><span class="lineno">  144</span>&#160;    GPU_FAISS_ASSERT(this-&gt;data_);</div>
<div class="line"><a name="l00145"></a><span class="lineno">  145</span>&#160;    GPU_FAISS_ASSERT(t.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a50411ce4d0fa32ef715e3321b6e33212">data</a>());</div>
<div class="line"><a name="l00146"></a><span class="lineno">  146</span>&#160;</div>
<div class="line"><a name="l00147"></a><span class="lineno">  147</span>&#160;    <span class="keywordtype">int</span> ourDev = getDeviceForAddress(this-&gt;data_);</div>
<div class="line"><a name="l00148"></a><span class="lineno">  148</span>&#160;    <span class="keywordtype">int</span> tDev = getDeviceForAddress(t.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a50411ce4d0fa32ef715e3321b6e33212">data</a>());</div>
<div class="line"><a name="l00149"></a><span class="lineno">  149</span>&#160;</div>
<div class="line"><a name="l00150"></a><span class="lineno">  150</span>&#160;    <span class="keywordflow">if</span> (tDev == -1) {</div>
<div class="line"><a name="l00151"></a><span class="lineno">  151</span>&#160;      CUDA_VERIFY(cudaMemcpyAsync(this-&gt;data_,</div>
<div class="line"><a name="l00152"></a><span class="lineno">  152</span>&#160;                                  t.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a50411ce4d0fa32ef715e3321b6e33212">data</a>(),</div>
<div class="line"><a name="l00153"></a><span class="lineno">  153</span>&#160;                                  this-&gt;getSizeInBytes(),</div>
<div class="line"><a name="l00154"></a><span class="lineno">  154</span>&#160;                                  ourDev == -1 ? cudaMemcpyHostToHost :</div>
<div class="line"><a name="l00155"></a><span class="lineno">  155</span>&#160;                                  cudaMemcpyHostToDevice,</div>
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<div class="line"><a name="l00158"></a><span class="lineno">  158</span>&#160;      CUDA_VERIFY(cudaMemcpyAsync(this-&gt;data_,</div>
<div class="line"><a name="l00159"></a><span class="lineno">  159</span>&#160;                                  t.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a50411ce4d0fa32ef715e3321b6e33212">data</a>(),</div>
<div class="line"><a name="l00160"></a><span class="lineno">  160</span>&#160;                                  this-&gt;getSizeInBytes(),</div>
<div class="line"><a name="l00161"></a><span class="lineno">  161</span>&#160;                                  ourDev == -1 ? cudaMemcpyDeviceToHost :</div>
<div class="line"><a name="l00162"></a><span class="lineno">  162</span>&#160;                                  cudaMemcpyDeviceToDevice,</div>
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<div class="line"><a name="l00164"></a><span class="lineno">  164</span>&#160;    }</div>
<div class="line"><a name="l00165"></a><span class="lineno">  165</span>&#160;  }</div>
<div class="line"><a name="l00166"></a><span class="lineno">  166</span>&#160;}</div>
<div class="line"><a name="l00167"></a><span class="lineno">  167</span>&#160;</div>
<div class="line"><a name="l00168"></a><span class="lineno">  168</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T, <span class="keywordtype">int</span> Dim, <span class="keywordtype">bool</span> InnerContig,</div>
<div class="line"><a name="l00169"></a><span class="lineno">  169</span>&#160;          <span class="keyword">typename</span> IndexT, <span class="keyword">template</span> &lt;<span class="keyword">typename</span> U&gt; <span class="keyword">class </span>PtrTraits&gt;</div>
<div class="line"><a name="l00170"></a><span class="lineno">  170</span>&#160;__host__ <span class="keywordtype">void</span></div>
<div class="line"><a name="l00171"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1Tensor.html#a6cc21376070a03d77661d6e333972c6a">  171</a></span>&#160;<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a6cc21376070a03d77661d6e333972c6a">Tensor&lt;T, Dim, InnerContig, IndexT, PtrTraits&gt;::copyTo</a>(</div>
<div class="line"><a name="l00172"></a><span class="lineno">  172</span>&#160;  <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor&lt;T, Dim, InnerContig, IndexT, PtrTraits&gt;</a>&amp; t,</div>
<div class="line"><a name="l00173"></a><span class="lineno">  173</span>&#160;  cudaStream_t stream) {</div>
<div class="line"><a name="l00174"></a><span class="lineno">  174</span>&#160;  <span class="comment">// The tensor must be fully contiguous</span></div>
<div class="line"><a name="l00175"></a><span class="lineno">  175</span>&#160;  GPU_FAISS_ASSERT(this-&gt;isContiguous());</div>
<div class="line"><a name="l00176"></a><span class="lineno">  176</span>&#160;</div>
<div class="line"><a name="l00177"></a><span class="lineno">  177</span>&#160;  <span class="comment">// Size must be the same (since dimensions are checked and</span></div>
<div class="line"><a name="l00178"></a><span class="lineno">  178</span>&#160;  <span class="comment">// continuity is assumed, we need only check total number of</span></div>
<div class="line"><a name="l00179"></a><span class="lineno">  179</span>&#160;  <span class="comment">// elements</span></div>
<div class="line"><a name="l00180"></a><span class="lineno">  180</span>&#160;  GPU_FAISS_ASSERT(this-&gt;numElements() == t.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a0ba9ab7c1676b7a41a6e6b2e5a490d2f">numElements</a>());</div>
<div class="line"><a name="l00181"></a><span class="lineno">  181</span>&#160;</div>
<div class="line"><a name="l00182"></a><span class="lineno">  182</span>&#160;  <span class="keywordflow">if</span> (t.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a0ba9ab7c1676b7a41a6e6b2e5a490d2f">numElements</a>() &gt; 0) {</div>
<div class="line"><a name="l00183"></a><span class="lineno">  183</span>&#160;    GPU_FAISS_ASSERT(this-&gt;data_);</div>
<div class="line"><a name="l00184"></a><span class="lineno">  184</span>&#160;    GPU_FAISS_ASSERT(t.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a50411ce4d0fa32ef715e3321b6e33212">data</a>());</div>
<div class="line"><a name="l00185"></a><span class="lineno">  185</span>&#160;</div>
<div class="line"><a name="l00186"></a><span class="lineno">  186</span>&#160;    <span class="keywordtype">int</span> ourDev = getDeviceForAddress(this-&gt;data_);</div>
<div class="line"><a name="l00187"></a><span class="lineno">  187</span>&#160;    <span class="keywordtype">int</span> tDev = getDeviceForAddress(t.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a50411ce4d0fa32ef715e3321b6e33212">data</a>());</div>
<div class="line"><a name="l00188"></a><span class="lineno">  188</span>&#160;</div>
<div class="line"><a name="l00189"></a><span class="lineno">  189</span>&#160;    <span class="keywordflow">if</span> (tDev == -1) {</div>
<div class="line"><a name="l00190"></a><span class="lineno">  190</span>&#160;      CUDA_VERIFY(cudaMemcpyAsync(t.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a50411ce4d0fa32ef715e3321b6e33212">data</a>(),</div>
<div class="line"><a name="l00191"></a><span class="lineno">  191</span>&#160;                                  this-&gt;data_,</div>
<div class="line"><a name="l00192"></a><span class="lineno">  192</span>&#160;                                  this-&gt;getSizeInBytes(),</div>
<div class="line"><a name="l00193"></a><span class="lineno">  193</span>&#160;                                  ourDev == -1 ? cudaMemcpyHostToHost :</div>
<div class="line"><a name="l00194"></a><span class="lineno">  194</span>&#160;                                  cudaMemcpyDeviceToHost,</div>
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<div class="line"><a name="l00196"></a><span class="lineno">  196</span>&#160;    } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00197"></a><span class="lineno">  197</span>&#160;      CUDA_VERIFY(cudaMemcpyAsync(t.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a50411ce4d0fa32ef715e3321b6e33212">data</a>(),</div>
<div class="line"><a name="l00198"></a><span class="lineno">  198</span>&#160;                                  this-&gt;data_,</div>
<div class="line"><a name="l00199"></a><span class="lineno">  199</span>&#160;                                  this-&gt;getSizeInBytes(),</div>
<div class="line"><a name="l00200"></a><span class="lineno">  200</span>&#160;                                  ourDev == -1 ? cudaMemcpyHostToDevice :</div>
<div class="line"><a name="l00201"></a><span class="lineno">  201</span>&#160;                                  cudaMemcpyDeviceToDevice,</div>
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<div class="line"><a name="l00203"></a><span class="lineno">  203</span>&#160;    }</div>
<div class="line"><a name="l00204"></a><span class="lineno">  204</span>&#160;  }</div>
<div class="line"><a name="l00205"></a><span class="lineno">  205</span>&#160;}</div>
<div class="line"><a name="l00206"></a><span class="lineno">  206</span>&#160;</div>
<div class="line"><a name="l00207"></a><span class="lineno">  207</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T, <span class="keywordtype">int</span> Dim, <span class="keywordtype">bool</span> InnerContig,</div>
<div class="line"><a name="l00208"></a><span class="lineno">  208</span>&#160;          <span class="keyword">typename</span> IndexT, <span class="keyword">template</span> &lt;<span class="keyword">typename</span> U&gt; <span class="keyword">class </span>PtrTraits&gt;</div>
<div class="line"><a name="l00209"></a><span class="lineno">  209</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> OtherT, <span class="keywordtype">int</span> OtherDim&gt;</div>
<div class="line"><a name="l00210"></a><span class="lineno">  210</span>&#160;__host__ __device__ <span class="keywordtype">bool</span></div>
<div class="line"><a name="l00211"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1Tensor.html#a3067941f8f8f09fc73e2f06243699825">  211</a></span>&#160;<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a3067941f8f8f09fc73e2f06243699825">Tensor&lt;T, Dim, InnerContig, IndexT, PtrTraits&gt;::isSame</a>(</div>
<div class="line"><a name="l00212"></a><span class="lineno">  212</span>&#160;  <span class="keyword">const</span> <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor&lt;OtherT, OtherDim, InnerContig, IndexT, PtrTraits&gt;</a>&amp; rhs)<span class="keyword"> const </span>{</div>
<div class="line"><a name="l00213"></a><span class="lineno">  213</span>&#160;  <span class="keywordflow">if</span> (Dim != OtherDim) {</div>
<div class="line"><a name="l00214"></a><span class="lineno">  214</span>&#160;    <span class="keywordflow">return</span> <span class="keyword">false</span>;</div>
<div class="line"><a name="l00215"></a><span class="lineno">  215</span>&#160;  }</div>
<div class="line"><a name="l00216"></a><span class="lineno">  216</span>&#160;</div>
<div class="line"><a name="l00217"></a><span class="lineno">  217</span>&#160;  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; Dim; ++i) {</div>
<div class="line"><a name="l00218"></a><span class="lineno">  218</span>&#160;    <span class="keywordflow">if</span> (this-&gt;getSize(i) != rhs.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a6699c311648457f257afa340c61f417c">getSize</a>(i)) {</div>
<div class="line"><a name="l00219"></a><span class="lineno">  219</span>&#160;      <span class="keywordflow">return</span> <span class="keyword">false</span>;</div>
<div class="line"><a name="l00220"></a><span class="lineno">  220</span>&#160;    }</div>
<div class="line"><a name="l00221"></a><span class="lineno">  221</span>&#160;</div>
<div class="line"><a name="l00222"></a><span class="lineno">  222</span>&#160;    <span class="keywordflow">if</span> (this-&gt;getStride(i) != rhs.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a0b8bba630f7a1fa217f90b20d298420a">getStride</a>(i)) {</div>
<div class="line"><a name="l00223"></a><span class="lineno">  223</span>&#160;      <span class="keywordflow">return</span> <span class="keyword">false</span>;</div>
<div class="line"><a name="l00224"></a><span class="lineno">  224</span>&#160;    }</div>
<div class="line"><a name="l00225"></a><span class="lineno">  225</span>&#160;  }</div>
<div class="line"><a name="l00226"></a><span class="lineno">  226</span>&#160;</div>
<div class="line"><a name="l00227"></a><span class="lineno">  227</span>&#160;  <span class="keywordflow">return</span> <span class="keyword">true</span>;</div>
<div class="line"><a name="l00228"></a><span class="lineno">  228</span>&#160;}</div>
<div class="line"><a name="l00229"></a><span class="lineno">  229</span>&#160;</div>
<div class="line"><a name="l00230"></a><span class="lineno">  230</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T, <span class="keywordtype">int</span> Dim, <span class="keywordtype">bool</span> InnerContig,</div>
<div class="line"><a name="l00231"></a><span class="lineno">  231</span>&#160;          <span class="keyword">typename</span> IndexT, <span class="keyword">template</span> &lt;<span class="keyword">typename</span> U&gt; <span class="keyword">class </span>PtrTraits&gt;</div>
<div class="line"><a name="l00232"></a><span class="lineno">  232</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> OtherT, <span class="keywordtype">int</span> OtherDim&gt;</div>
<div class="line"><a name="l00233"></a><span class="lineno">  233</span>&#160;__host__ __device__ <span class="keywordtype">bool</span></div>
<div class="line"><a name="l00234"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1Tensor.html#a22c1e45f81f7f9e5427e2eed19f9cd11">  234</a></span>&#160;<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a22c1e45f81f7f9e5427e2eed19f9cd11">Tensor&lt;T, Dim, InnerContig, IndexT, PtrTraits&gt;::isSameSize</a>(</div>
<div class="line"><a name="l00235"></a><span class="lineno">  235</span>&#160;  <span class="keyword">const</span> <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor&lt;OtherT, OtherDim, InnerContig, IndexT, PtrTraits&gt;</a>&amp; rhs)<span class="keyword"> const </span>{</div>
<div class="line"><a name="l00236"></a><span class="lineno">  236</span>&#160;  <span class="keywordflow">if</span> (Dim != OtherDim) {</div>
<div class="line"><a name="l00237"></a><span class="lineno">  237</span>&#160;    <span class="keywordflow">return</span> <span class="keyword">false</span>;</div>
<div class="line"><a name="l00238"></a><span class="lineno">  238</span>&#160;  }</div>
<div class="line"><a name="l00239"></a><span class="lineno">  239</span>&#160;</div>
<div class="line"><a name="l00240"></a><span class="lineno">  240</span>&#160;  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; Dim; ++i) {</div>
<div class="line"><a name="l00241"></a><span class="lineno">  241</span>&#160;    <span class="keywordflow">if</span> (this-&gt;getSize(i) != rhs.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a6699c311648457f257afa340c61f417c">getSize</a>(i)) {</div>
<div class="line"><a name="l00242"></a><span class="lineno">  242</span>&#160;      <span class="keywordflow">return</span> <span class="keyword">false</span>;</div>
<div class="line"><a name="l00243"></a><span class="lineno">  243</span>&#160;    }</div>
<div class="line"><a name="l00244"></a><span class="lineno">  244</span>&#160;  }</div>
<div class="line"><a name="l00245"></a><span class="lineno">  245</span>&#160;</div>
<div class="line"><a name="l00246"></a><span class="lineno">  246</span>&#160;  <span class="keywordflow">return</span> <span class="keyword">true</span>;</div>
<div class="line"><a name="l00247"></a><span class="lineno">  247</span>&#160;}</div>
<div class="line"><a name="l00248"></a><span class="lineno">  248</span>&#160;</div>
<div class="line"><a name="l00249"></a><span class="lineno">  249</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T, <span class="keywordtype">int</span> Dim, <span class="keywordtype">bool</span> InnerContig,</div>
<div class="line"><a name="l00250"></a><span class="lineno">  250</span>&#160;          <span class="keyword">typename</span> IndexT, <span class="keyword">template</span> &lt;<span class="keyword">typename</span> U&gt; <span class="keyword">class </span>PtrTraits&gt;</div>
<div class="line"><a name="l00251"></a><span class="lineno">  251</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> U&gt;</div>
<div class="line"><a name="l00252"></a><span class="lineno">  252</span>&#160;__host__ __device__ <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor&lt;U, Dim, InnerContig, IndexT, PtrTraits&gt;</a></div>
<div class="line"><a name="l00253"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1Tensor.html#a2894f8fdfab8ec3245364a6f9e8a5259">  253</a></span>&#160;<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a2894f8fdfab8ec3245364a6f9e8a5259">Tensor&lt;T, Dim, InnerContig, IndexT, PtrTraits&gt;::cast</a>() {</div>
<div class="line"><a name="l00254"></a><span class="lineno">  254</span>&#160;  static_assert(<span class="keyword">sizeof</span>(U) == <span class="keyword">sizeof</span>(T), <span class="stringliteral">&quot;cast must be to same size object&quot;</span>);</div>
<div class="line"><a name="l00255"></a><span class="lineno">  255</span>&#160;</div>
<div class="line"><a name="l00256"></a><span class="lineno">  256</span>&#160;  <span class="keywordflow">return</span> <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor&lt;U, Dim, InnerContig, IndexT, PtrTraits&gt;</a>(</div>
<div class="line"><a name="l00257"></a><span class="lineno">  257</span>&#160;    <span class="keyword">reinterpret_cast&lt;</span>U*<span class="keyword">&gt;</span>(data_), size_, stride_);</div>
<div class="line"><a name="l00258"></a><span class="lineno">  258</span>&#160;}</div>
<div class="line"><a name="l00259"></a><span class="lineno">  259</span>&#160;</div>
<div class="line"><a name="l00260"></a><span class="lineno">  260</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T, <span class="keywordtype">int</span> Dim, <span class="keywordtype">bool</span> InnerContig,</div>
<div class="line"><a name="l00261"></a><span class="lineno">  261</span>&#160;          <span class="keyword">typename</span> IndexT, <span class="keyword">template</span> &lt;<span class="keyword">typename</span> U&gt; <span class="keyword">class </span>PtrTraits&gt;</div>
<div class="line"><a name="l00262"></a><span class="lineno">  262</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> U&gt;</div>
<div class="line"><a name="l00263"></a><span class="lineno">  263</span>&#160;__host__ __device__ <span class="keyword">const</span> <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor&lt;U, Dim, InnerContig, IndexT, PtrTraits&gt;</a></div>
<div class="line"><a name="l00264"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1Tensor.html#a79a16bd4300ca8fdba52932c7c97cce9">  264</a></span>&#160;<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a2894f8fdfab8ec3245364a6f9e8a5259">Tensor&lt;T, Dim, InnerContig, IndexT, PtrTraits&gt;::cast</a>()<span class="keyword"> const </span>{</div>
<div class="line"><a name="l00265"></a><span class="lineno">  265</span>&#160;  static_assert(<span class="keyword">sizeof</span>(U) == <span class="keyword">sizeof</span>(T), <span class="stringliteral">&quot;cast must be to same size object&quot;</span>);</div>
<div class="line"><a name="l00266"></a><span class="lineno">  266</span>&#160;</div>
<div class="line"><a name="l00267"></a><span class="lineno">  267</span>&#160;  <span class="keywordflow">return</span> <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor&lt;U, Dim, InnerContig, IndexT, PtrTraits&gt;</a>(</div>
<div class="line"><a name="l00268"></a><span class="lineno">  268</span>&#160;    <span class="keyword">reinterpret_cast&lt;</span>U*<span class="keyword">&gt;</span>(data_), size_, stride_);</div>
<div class="line"><a name="l00269"></a><span class="lineno">  269</span>&#160;}</div>
<div class="line"><a name="l00270"></a><span class="lineno">  270</span>&#160;</div>
<div class="line"><a name="l00271"></a><span class="lineno">  271</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T, <span class="keywordtype">int</span> Dim, <span class="keywordtype">bool</span> InnerContig,</div>
<div class="line"><a name="l00272"></a><span class="lineno">  272</span>&#160;          <span class="keyword">typename</span> IndexT, <span class="keyword">template</span> &lt;<span class="keyword">typename</span> U&gt; <span class="keyword">class </span>PtrTraits&gt;</div>
<div class="line"><a name="l00273"></a><span class="lineno">  273</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> U&gt;</div>
<div class="line"><a name="l00274"></a><span class="lineno">  274</span>&#160;__host__ __device__ <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor&lt;U, Dim, InnerContig, IndexT, PtrTraits&gt;</a></div>
<div class="line"><a name="l00275"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1Tensor.html#a6c9640c365134ccc33cdb2695b016eb3">  275</a></span>&#160;<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a6c9640c365134ccc33cdb2695b016eb3">Tensor&lt;T, Dim, InnerContig, IndexT, PtrTraits&gt;::castResize</a>() {</div>
<div class="line"><a name="l00276"></a><span class="lineno">  276</span>&#160;  static_assert(<span class="keyword">sizeof</span>(U) &gt;= <span class="keyword">sizeof</span>(T), <span class="stringliteral">&quot;only handles greater sizes&quot;</span>);</div>
<div class="line"><a name="l00277"></a><span class="lineno">  277</span>&#160;  constexpr <span class="keywordtype">int</span> kMultiple = <span class="keyword">sizeof</span>(U) / <span class="keyword">sizeof</span>(T);</div>
<div class="line"><a name="l00278"></a><span class="lineno">  278</span>&#160;</div>
<div class="line"><a name="l00279"></a><span class="lineno">  279</span>&#160;  GPU_FAISS_ASSERT(canCastResize&lt;U&gt;());</div>
<div class="line"><a name="l00280"></a><span class="lineno">  280</span>&#160;</div>
<div class="line"><a name="l00281"></a><span class="lineno">  281</span>&#160;  IndexT newSize[Dim];</div>
<div class="line"><a name="l00282"></a><span class="lineno">  282</span>&#160;  IndexT newStride[Dim];</div>
<div class="line"><a name="l00283"></a><span class="lineno">  283</span>&#160;</div>
<div class="line"><a name="l00284"></a><span class="lineno">  284</span>&#160;  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; Dim - 1; ++i) {</div>
<div class="line"><a name="l00285"></a><span class="lineno">  285</span>&#160;    newSize[i] = size_[i];</div>
<div class="line"><a name="l00286"></a><span class="lineno">  286</span>&#160;    newStride[i] = stride_[i] / kMultiple;</div>
<div class="line"><a name="l00287"></a><span class="lineno">  287</span>&#160;  }</div>
<div class="line"><a name="l00288"></a><span class="lineno">  288</span>&#160;</div>
<div class="line"><a name="l00289"></a><span class="lineno">  289</span>&#160;  newStride[Dim - 1] = 1; <span class="comment">// this is the same as the old stride</span></div>
<div class="line"><a name="l00290"></a><span class="lineno">  290</span>&#160;  newSize[Dim - 1] = size_[Dim - 1] / kMultiple;</div>
<div class="line"><a name="l00291"></a><span class="lineno">  291</span>&#160;</div>
<div class="line"><a name="l00292"></a><span class="lineno">  292</span>&#160;  <span class="keywordflow">return</span> <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor&lt;U, Dim, InnerContig, IndexT, PtrTraits&gt;</a>(</div>
<div class="line"><a name="l00293"></a><span class="lineno">  293</span>&#160;    <span class="keyword">reinterpret_cast&lt;</span>U*<span class="keyword">&gt;</span>(data_), newSize, newStride);</div>
<div class="line"><a name="l00294"></a><span class="lineno">  294</span>&#160;}</div>
<div class="line"><a name="l00295"></a><span class="lineno">  295</span>&#160;</div>
<div class="line"><a name="l00296"></a><span class="lineno">  296</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T, <span class="keywordtype">int</span> Dim, <span class="keywordtype">bool</span> InnerContig,</div>
<div class="line"><a name="l00297"></a><span class="lineno">  297</span>&#160;          <span class="keyword">typename</span> IndexT, <span class="keyword">template</span> &lt;<span class="keyword">typename</span> U&gt; <span class="keyword">class </span>PtrTraits&gt;</div>
<div class="line"><a name="l00298"></a><span class="lineno">  298</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> U&gt;</div>
<div class="line"><a name="l00299"></a><span class="lineno">  299</span>&#160;__host__ __device__ <span class="keyword">const</span> <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor&lt;U, Dim, InnerContig, IndexT, PtrTraits&gt;</a></div>
<div class="line"><a name="l00300"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1Tensor.html#ae06338d9b19c62452c2111682447f863">  300</a></span>&#160;<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a6c9640c365134ccc33cdb2695b016eb3">Tensor&lt;T, Dim, InnerContig, IndexT, PtrTraits&gt;::castResize</a>()<span class="keyword"> const </span>{</div>
<div class="line"><a name="l00301"></a><span class="lineno">  301</span>&#160;  <span class="keywordflow">return</span> <span class="keyword">const_cast&lt;</span><a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor&lt;T, Dim, InnerContig, IndexT, PtrTraits&gt;</a>*<span class="keyword">&gt;</span>(<span class="keyword">this</span>)-&gt;</div>
<div class="line"><a name="l00302"></a><span class="lineno">  302</span>&#160;    castResize&lt;U&gt;();</div>
<div class="line"><a name="l00303"></a><span class="lineno">  303</span>&#160;}</div>
<div class="line"><a name="l00304"></a><span class="lineno">  304</span>&#160;</div>
<div class="line"><a name="l00305"></a><span class="lineno">  305</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T, <span class="keywordtype">int</span> Dim, <span class="keywordtype">bool</span> InnerContig,</div>
<div class="line"><a name="l00306"></a><span class="lineno">  306</span>&#160;          <span class="keyword">typename</span> IndexT, <span class="keyword">template</span> &lt;<span class="keyword">typename</span> U&gt; <span class="keyword">class </span>PtrTraits&gt;</div>
<div class="line"><a name="l00307"></a><span class="lineno">  307</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> U&gt;</div>
<div class="line"><a name="l00308"></a><span class="lineno">  308</span>&#160;__host__ __device__ <span class="keywordtype">bool</span></div>
<div class="line"><a name="l00309"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1Tensor.html#a7fbbf51f8ef6bea9cc863a86e20d994e">  309</a></span>&#160;<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a7fbbf51f8ef6bea9cc863a86e20d994e">Tensor&lt;T, Dim, InnerContig, IndexT, PtrTraits&gt;::canCastResize</a>()<span class="keyword"> const </span>{</div>
<div class="line"><a name="l00310"></a><span class="lineno">  310</span>&#160;  static_assert(<span class="keyword">sizeof</span>(U) &gt;= <span class="keyword">sizeof</span>(T), <span class="stringliteral">&quot;only handles greater sizes&quot;</span>);</div>
<div class="line"><a name="l00311"></a><span class="lineno">  311</span>&#160;  constexpr <span class="keywordtype">int</span> kMultiple = <span class="keyword">sizeof</span>(U) / <span class="keyword">sizeof</span>(T);</div>
<div class="line"><a name="l00312"></a><span class="lineno">  312</span>&#160;</div>
<div class="line"><a name="l00313"></a><span class="lineno">  313</span>&#160;  <span class="comment">// Ensure that the base pointer is sizeof(U) aligned</span></div>
<div class="line"><a name="l00314"></a><span class="lineno">  314</span>&#160;  <span class="keywordflow">if</span> (((uintptr_t) data_) % <span class="keyword">sizeof</span>(U) != 0) {</div>
<div class="line"><a name="l00315"></a><span class="lineno">  315</span>&#160;    <span class="keywordflow">return</span> <span class="keyword">false</span>;</div>
<div class="line"><a name="l00316"></a><span class="lineno">  316</span>&#160;  }</div>
<div class="line"><a name="l00317"></a><span class="lineno">  317</span>&#160;</div>
<div class="line"><a name="l00318"></a><span class="lineno">  318</span>&#160;  <span class="comment">// Check all outer strides</span></div>
<div class="line"><a name="l00319"></a><span class="lineno">  319</span>&#160;  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; Dim - 1; ++i) {</div>
<div class="line"><a name="l00320"></a><span class="lineno">  320</span>&#160;    <span class="keywordflow">if</span> (stride_[i] % kMultiple != 0) {</div>
<div class="line"><a name="l00321"></a><span class="lineno">  321</span>&#160;      <span class="keywordflow">return</span> <span class="keyword">false</span>;</div>
<div class="line"><a name="l00322"></a><span class="lineno">  322</span>&#160;    }</div>
<div class="line"><a name="l00323"></a><span class="lineno">  323</span>&#160;  }</div>
<div class="line"><a name="l00324"></a><span class="lineno">  324</span>&#160;</div>
<div class="line"><a name="l00325"></a><span class="lineno">  325</span>&#160;  <span class="comment">// Check inner size</span></div>
<div class="line"><a name="l00326"></a><span class="lineno">  326</span>&#160;  <span class="keywordflow">if</span> (size_[Dim - 1] % kMultiple != 0) {</div>
<div class="line"><a name="l00327"></a><span class="lineno">  327</span>&#160;    <span class="keywordflow">return</span> <span class="keyword">false</span>;</div>
<div class="line"><a name="l00328"></a><span class="lineno">  328</span>&#160;  }</div>
<div class="line"><a name="l00329"></a><span class="lineno">  329</span>&#160;</div>
<div class="line"><a name="l00330"></a><span class="lineno">  330</span>&#160;  <span class="keywordflow">if</span> (stride_[Dim - 1] != 1) {</div>
<div class="line"><a name="l00331"></a><span class="lineno">  331</span>&#160;    <span class="keywordflow">return</span> <span class="keyword">false</span>;</div>
<div class="line"><a name="l00332"></a><span class="lineno">  332</span>&#160;  }</div>
<div class="line"><a name="l00333"></a><span class="lineno">  333</span>&#160;</div>
<div class="line"><a name="l00334"></a><span class="lineno">  334</span>&#160;  <span class="keywordflow">return</span> <span class="keyword">true</span>;</div>
<div class="line"><a name="l00335"></a><span class="lineno">  335</span>&#160;}</div>
<div class="line"><a name="l00336"></a><span class="lineno">  336</span>&#160;</div>
<div class="line"><a name="l00337"></a><span class="lineno">  337</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T, <span class="keywordtype">int</span> Dim, <span class="keywordtype">bool</span> InnerContig,</div>
<div class="line"><a name="l00338"></a><span class="lineno">  338</span>&#160;          <span class="keyword">typename</span> IndexT, <span class="keyword">template</span> &lt;<span class="keyword">typename</span> U&gt; <span class="keyword">class </span>PtrTraits&gt;</div>
<div class="line"><a name="l00339"></a><span class="lineno">  339</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> NewIndexT&gt;</div>
<div class="line"><a name="l00340"></a><span class="lineno">  340</span>&#160;__host__ <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor&lt;T, Dim, InnerContig, NewIndexT, PtrTraits&gt;</a></div>
<div class="line"><a name="l00341"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1Tensor.html#a9f0c817e9751fe02926c2346a97f0350">  341</a></span>&#160;<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a9f0c817e9751fe02926c2346a97f0350">Tensor&lt;T, Dim, InnerContig, IndexT, PtrTraits&gt;::castIndexType</a>()<span class="keyword"> const </span>{</div>
<div class="line"><a name="l00342"></a><span class="lineno">  342</span>&#160;  <span class="keywordflow">if</span> (<span class="keyword">sizeof</span>(NewIndexT) &lt; <span class="keyword">sizeof</span>(IndexT)) {</div>
<div class="line"><a name="l00343"></a><span class="lineno">  343</span>&#160;    GPU_FAISS_ASSERT(this-&gt;canUseIndexType&lt;NewIndexT&gt;());</div>
<div class="line"><a name="l00344"></a><span class="lineno">  344</span>&#160;  }</div>
<div class="line"><a name="l00345"></a><span class="lineno">  345</span>&#160;</div>
<div class="line"><a name="l00346"></a><span class="lineno">  346</span>&#160;  NewIndexT newSize[Dim];</div>
<div class="line"><a name="l00347"></a><span class="lineno">  347</span>&#160;  NewIndexT newStride[Dim];</div>
<div class="line"><a name="l00348"></a><span class="lineno">  348</span>&#160;  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; Dim; ++i) {</div>
<div class="line"><a name="l00349"></a><span class="lineno">  349</span>&#160;    newSize[i] = (NewIndexT) size_[i];</div>
<div class="line"><a name="l00350"></a><span class="lineno">  350</span>&#160;    newStride[i] = (NewIndexT) stride_[i];</div>
<div class="line"><a name="l00351"></a><span class="lineno">  351</span>&#160;  }</div>
<div class="line"><a name="l00352"></a><span class="lineno">  352</span>&#160;</div>
<div class="line"><a name="l00353"></a><span class="lineno">  353</span>&#160;  <span class="keywordflow">return</span> <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor&lt;T, Dim, InnerContig, NewIndexT, PtrTraits&gt;</a>(</div>
<div class="line"><a name="l00354"></a><span class="lineno">  354</span>&#160;    data_, newSize, newStride);</div>
<div class="line"><a name="l00355"></a><span class="lineno">  355</span>&#160;}</div>
<div class="line"><a name="l00356"></a><span class="lineno">  356</span>&#160;</div>
<div class="line"><a name="l00357"></a><span class="lineno">  357</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T, <span class="keywordtype">int</span> Dim, <span class="keywordtype">bool</span> InnerContig,</div>
<div class="line"><a name="l00358"></a><span class="lineno">  358</span>&#160;          <span class="keyword">typename</span> IndexT, <span class="keyword">template</span> &lt;<span class="keyword">typename</span> U&gt; <span class="keyword">class </span>PtrTraits&gt;</div>
<div class="line"><a name="l00359"></a><span class="lineno">  359</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> NewIndexT&gt;</div>
<div class="line"><a name="l00360"></a><span class="lineno">  360</span>&#160;__host__ <span class="keywordtype">bool</span></div>
<div class="line"><a name="l00361"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1Tensor.html#a2ac9dc9fa8d81f2651a1be486c14ba62">  361</a></span>&#160;<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a2ac9dc9fa8d81f2651a1be486c14ba62">Tensor&lt;T, Dim, InnerContig, IndexT, PtrTraits&gt;::canUseIndexType</a>()<span class="keyword"> const </span>{</div>
<div class="line"><a name="l00362"></a><span class="lineno">  362</span>&#160;  static_assert(<span class="keyword">sizeof</span>(<span class="keywordtype">size_t</span>) &gt;= <span class="keyword">sizeof</span>(IndexT),</div>
<div class="line"><a name="l00363"></a><span class="lineno">  363</span>&#160;                <span class="stringliteral">&quot;index size too large&quot;</span>);</div>
<div class="line"><a name="l00364"></a><span class="lineno">  364</span>&#160;  static_assert(<span class="keyword">sizeof</span>(<span class="keywordtype">size_t</span>) &gt;= <span class="keyword">sizeof</span>(NewIndexT),</div>
<div class="line"><a name="l00365"></a><span class="lineno">  365</span>&#160;                <span class="stringliteral">&quot;new index size too large&quot;</span>);</div>
<div class="line"><a name="l00366"></a><span class="lineno">  366</span>&#160;</div>
<div class="line"><a name="l00367"></a><span class="lineno">  367</span>&#160;  <span class="comment">// Find maximum offset that can be calculated</span></div>
<div class="line"><a name="l00368"></a><span class="lineno">  368</span>&#160;  <span class="comment">// FIXME: maybe also consider offset in bytes? multiply by sizeof(T)?</span></div>
<div class="line"><a name="l00369"></a><span class="lineno">  369</span>&#160;  <span class="keywordtype">size_t</span> maxOffset = 0;</div>
<div class="line"><a name="l00370"></a><span class="lineno">  370</span>&#160;</div>
<div class="line"><a name="l00371"></a><span class="lineno">  371</span>&#160;  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; Dim; ++i) {</div>
<div class="line"><a name="l00372"></a><span class="lineno">  372</span>&#160;    <span class="keywordtype">size_t</span> curMaxOffset = (size_t) size_[i] * (<span class="keywordtype">size_t</span>) stride_[i];</div>
<div class="line"><a name="l00373"></a><span class="lineno">  373</span>&#160;    <span class="keywordflow">if</span> (curMaxOffset &gt; maxOffset) {</div>
<div class="line"><a name="l00374"></a><span class="lineno">  374</span>&#160;      maxOffset = curMaxOffset;</div>
<div class="line"><a name="l00375"></a><span class="lineno">  375</span>&#160;    }</div>
<div class="line"><a name="l00376"></a><span class="lineno">  376</span>&#160;  }</div>
<div class="line"><a name="l00377"></a><span class="lineno">  377</span>&#160;</div>
<div class="line"><a name="l00378"></a><span class="lineno">  378</span>&#160;  <span class="keywordflow">if</span> (maxOffset &gt; (<span class="keywordtype">size_t</span>) std::numeric_limits&lt;NewIndexT&gt;::max()) {</div>
<div class="line"><a name="l00379"></a><span class="lineno">  379</span>&#160;    <span class="keywordflow">return</span> <span class="keyword">false</span>;</div>
<div class="line"><a name="l00380"></a><span class="lineno">  380</span>&#160;  }</div>
<div class="line"><a name="l00381"></a><span class="lineno">  381</span>&#160;</div>
<div class="line"><a name="l00382"></a><span class="lineno">  382</span>&#160;  <span class="keywordflow">return</span> <span class="keyword">true</span>;</div>
<div class="line"><a name="l00383"></a><span class="lineno">  383</span>&#160;}</div>
<div class="line"><a name="l00384"></a><span class="lineno">  384</span>&#160;</div>
<div class="line"><a name="l00385"></a><span class="lineno">  385</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T, <span class="keywordtype">int</span> Dim, <span class="keywordtype">bool</span> InnerContig,</div>
<div class="line"><a name="l00386"></a><span class="lineno">  386</span>&#160;          <span class="keyword">typename</span> IndexT, <span class="keyword">template</span> &lt;<span class="keyword">typename</span> U&gt; <span class="keyword">class </span>PtrTraits&gt;</div>
<div class="line"><a name="l00387"></a><span class="lineno">  387</span>&#160;__host__ __device__ <span class="keywordtype">size_t</span></div>
<div class="line"><a name="l00388"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1Tensor.html#a0ba9ab7c1676b7a41a6e6b2e5a490d2f">  388</a></span>&#160;<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a0ba9ab7c1676b7a41a6e6b2e5a490d2f">Tensor&lt;T, Dim, InnerContig, IndexT, PtrTraits&gt;::numElements</a>()<span class="keyword"> const </span>{</div>
<div class="line"><a name="l00389"></a><span class="lineno">  389</span>&#160;  <span class="keywordtype">size_t</span> size = (size_t) getSize(0);</div>
<div class="line"><a name="l00390"></a><span class="lineno">  390</span>&#160;</div>
<div class="line"><a name="l00391"></a><span class="lineno">  391</span>&#160;  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 1; i &lt; Dim; ++i) {</div>
<div class="line"><a name="l00392"></a><span class="lineno">  392</span>&#160;    size *= (size_t) getSize(i);</div>
<div class="line"><a name="l00393"></a><span class="lineno">  393</span>&#160;  }</div>
<div class="line"><a name="l00394"></a><span class="lineno">  394</span>&#160;</div>
<div class="line"><a name="l00395"></a><span class="lineno">  395</span>&#160;  <span class="keywordflow">return</span> size;</div>
<div class="line"><a name="l00396"></a><span class="lineno">  396</span>&#160;}</div>
<div class="line"><a name="l00397"></a><span class="lineno">  397</span>&#160;</div>
<div class="line"><a name="l00398"></a><span class="lineno">  398</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T, <span class="keywordtype">int</span> Dim, <span class="keywordtype">bool</span> InnerContig,</div>
<div class="line"><a name="l00399"></a><span class="lineno">  399</span>&#160;          <span class="keyword">typename</span> IndexT, <span class="keyword">template</span> &lt;<span class="keyword">typename</span> U&gt; <span class="keyword">class </span>PtrTraits&gt;</div>
<div class="line"><a name="l00400"></a><span class="lineno">  400</span>&#160;__host__ __device__ <span class="keywordtype">bool</span></div>
<div class="line"><a name="l00401"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1Tensor.html#a09019c54911db891c9321fd3b34509c2">  401</a></span>&#160;<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a09019c54911db891c9321fd3b34509c2">Tensor&lt;T, Dim, InnerContig, IndexT, PtrTraits&gt;::isContiguous</a>()<span class="keyword"> const </span>{</div>
<div class="line"><a name="l00402"></a><span class="lineno">  402</span>&#160;  <span class="keywordtype">long</span> prevSize = 1;</div>
<div class="line"><a name="l00403"></a><span class="lineno">  403</span>&#160;</div>
<div class="line"><a name="l00404"></a><span class="lineno">  404</span>&#160;  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = Dim - 1; i &gt;= 0; --i) {</div>
<div class="line"><a name="l00405"></a><span class="lineno">  405</span>&#160;    <span class="keywordflow">if</span> (getSize(i) != (IndexT) 1) {</div>
<div class="line"><a name="l00406"></a><span class="lineno">  406</span>&#160;      <span class="keywordflow">if</span> (getStride(i) == prevSize) {</div>
<div class="line"><a name="l00407"></a><span class="lineno">  407</span>&#160;        prevSize *= getSize(i);</div>
<div class="line"><a name="l00408"></a><span class="lineno">  408</span>&#160;      } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00409"></a><span class="lineno">  409</span>&#160;        <span class="keywordflow">return</span> <span class="keyword">false</span>;</div>
<div class="line"><a name="l00410"></a><span class="lineno">  410</span>&#160;      }</div>
<div class="line"><a name="l00411"></a><span class="lineno">  411</span>&#160;    }</div>
<div class="line"><a name="l00412"></a><span class="lineno">  412</span>&#160;  }</div>
<div class="line"><a name="l00413"></a><span class="lineno">  413</span>&#160;</div>
<div class="line"><a name="l00414"></a><span class="lineno">  414</span>&#160;  <span class="keywordflow">return</span> <span class="keyword">true</span>;</div>
<div class="line"><a name="l00415"></a><span class="lineno">  415</span>&#160;}</div>
<div class="line"><a name="l00416"></a><span class="lineno">  416</span>&#160;</div>
<div class="line"><a name="l00417"></a><span class="lineno">  417</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T, <span class="keywordtype">int</span> Dim, <span class="keywordtype">bool</span> InnerContig,</div>
<div class="line"><a name="l00418"></a><span class="lineno">  418</span>&#160;          <span class="keyword">typename</span> IndexT, <span class="keyword">template</span> &lt;<span class="keyword">typename</span> U&gt; <span class="keyword">class </span>PtrTraits&gt;</div>
<div class="line"><a name="l00419"></a><span class="lineno">  419</span>&#160;__host__ __device__ <span class="keywordtype">bool</span></div>
<div class="line"><a name="l00420"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1Tensor.html#a663e3829c395372acdc8d2e71c0bdabe">  420</a></span>&#160;<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor&lt;T, Dim, InnerContig, IndexT, PtrTraits&gt;::isConsistentlySized</a>(<span class="keywordtype">int</span> i)<span class="keyword"> const </span>{</div>
<div class="line"><a name="l00421"></a><span class="lineno">  421</span>&#160;  <span class="keywordflow">if</span> (i == 0 &amp;&amp; getStride(i) &gt; 0 &amp;&amp; getSize(i) &gt; 0) {</div>
<div class="line"><a name="l00422"></a><span class="lineno">  422</span>&#160;    <span class="keywordflow">return</span> <span class="keyword">true</span>;</div>
<div class="line"><a name="l00423"></a><span class="lineno">  423</span>&#160;  } <span class="keywordflow">else</span> <span class="keywordflow">if</span> ((i &gt; 0) &amp;&amp; (i &lt; Dim) &amp;&amp; (getStride(i) &gt; 0) &amp;&amp;</div>
<div class="line"><a name="l00424"></a><span class="lineno">  424</span>&#160;             ((getStride(i - 1) / getStride(i)) &gt;= getSize(i))) {</div>
<div class="line"><a name="l00425"></a><span class="lineno">  425</span>&#160;    <span class="keywordflow">return</span> <span class="keyword">true</span>;</div>
<div class="line"><a name="l00426"></a><span class="lineno">  426</span>&#160;  }</div>
<div class="line"><a name="l00427"></a><span class="lineno">  427</span>&#160;</div>
<div class="line"><a name="l00428"></a><span class="lineno">  428</span>&#160;  <span class="keywordflow">return</span> <span class="keyword">false</span>;</div>
<div class="line"><a name="l00429"></a><span class="lineno">  429</span>&#160;}</div>
<div class="line"><a name="l00430"></a><span class="lineno">  430</span>&#160;</div>
<div class="line"><a name="l00431"></a><span class="lineno">  431</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T, <span class="keywordtype">int</span> Dim, <span class="keywordtype">bool</span> InnerContig,</div>
<div class="line"><a name="l00432"></a><span class="lineno">  432</span>&#160;          <span class="keyword">typename</span> IndexT, <span class="keyword">template</span> &lt;<span class="keyword">typename</span> U&gt; <span class="keyword">class </span>PtrTraits&gt;</div>
<div class="line"><a name="l00433"></a><span class="lineno">  433</span>&#160;__host__ __device__ <span class="keywordtype">bool</span></div>
<div class="line"><a name="l00434"></a><span class="lineno">  434</span>&#160;<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor&lt;T, Dim, InnerContig, IndexT, PtrTraits&gt;::isConsistentlySized</a>()<span class="keyword"> const </span>{</div>
<div class="line"><a name="l00435"></a><span class="lineno">  435</span>&#160;  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; Dim; ++i) {</div>
<div class="line"><a name="l00436"></a><span class="lineno">  436</span>&#160;    <span class="keywordflow">if</span> (!isConsistentlySized(i)) {</div>
<div class="line"><a name="l00437"></a><span class="lineno">  437</span>&#160;      <span class="keywordflow">return</span> <span class="keyword">false</span>;</div>
<div class="line"><a name="l00438"></a><span class="lineno">  438</span>&#160;    }</div>
<div class="line"><a name="l00439"></a><span class="lineno">  439</span>&#160;  }</div>
<div class="line"><a name="l00440"></a><span class="lineno">  440</span>&#160;</div>
<div class="line"><a name="l00441"></a><span class="lineno">  441</span>&#160;  <span class="keywordflow">return</span> <span class="keyword">true</span>;</div>
<div class="line"><a name="l00442"></a><span class="lineno">  442</span>&#160;}</div>
<div class="line"><a name="l00443"></a><span class="lineno">  443</span>&#160;</div>
<div class="line"><a name="l00444"></a><span class="lineno">  444</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T, <span class="keywordtype">int</span> Dim, <span class="keywordtype">bool</span> InnerContig,</div>
<div class="line"><a name="l00445"></a><span class="lineno">  445</span>&#160;          <span class="keyword">typename</span> IndexT, <span class="keyword">template</span> &lt;<span class="keyword">typename</span> U&gt; <span class="keyword">class </span>PtrTraits&gt;</div>
<div class="line"><a name="l00446"></a><span class="lineno">  446</span>&#160;__host__ __device__ <span class="keywordtype">bool</span></div>
<div class="line"><a name="l00447"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1Tensor.html#a3f4e3c6afdf4a03308756b6ae6462c38">  447</a></span>&#160;<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a3f4e3c6afdf4a03308756b6ae6462c38">Tensor&lt;T, Dim, InnerContig, IndexT, PtrTraits&gt;::isContiguousDim</a>(<span class="keywordtype">int</span> i)<span class="keyword"> const </span>{</div>
<div class="line"><a name="l00448"></a><span class="lineno">  448</span>&#160;  <span class="keywordflow">return</span> (i == Dim - 1) || <span class="comment">// just in case</span></div>
<div class="line"><a name="l00449"></a><span class="lineno">  449</span>&#160;    ((i &lt; Dim - 1) &amp;&amp;</div>
<div class="line"><a name="l00450"></a><span class="lineno">  450</span>&#160;     ((getStride(i) / getStride(i + 1)) == getSize(i + 1)));</div>
<div class="line"><a name="l00451"></a><span class="lineno">  451</span>&#160;}</div>
<div class="line"><a name="l00452"></a><span class="lineno">  452</span>&#160;</div>
<div class="line"><a name="l00453"></a><span class="lineno">  453</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T, <span class="keywordtype">int</span> Dim, <span class="keywordtype">bool</span> InnerContig,</div>
<div class="line"><a name="l00454"></a><span class="lineno">  454</span>&#160;          <span class="keyword">typename</span> IndexT, <span class="keyword">template</span> &lt;<span class="keyword">typename</span> U&gt; <span class="keyword">class </span>PtrTraits&gt;</div>
<div class="line"><a name="l00455"></a><span class="lineno">  455</span>&#160;__host__ __device__ <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor&lt;T, Dim, InnerContig, IndexT, PtrTraits&gt;</a></div>
<div class="line"><a name="l00456"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1Tensor.html#a82a3484a6458e3e95bb91d320f2c6731">  456</a></span>&#160;<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a82a3484a6458e3e95bb91d320f2c6731">Tensor&lt;T, Dim, InnerContig, IndexT, PtrTraits&gt;::transpose</a>(<span class="keywordtype">int</span> dim1,</div>
<div class="line"><a name="l00457"></a><span class="lineno">  457</span>&#160;                                                     <span class="keywordtype">int</span> dim2)<span class="keyword"> const </span>{</div>
<div class="line"><a name="l00458"></a><span class="lineno">  458</span>&#160;  GPU_FAISS_ASSERT(dim1 &gt;= 0 &amp;&amp; dim1 &lt; Dim);</div>
<div class="line"><a name="l00459"></a><span class="lineno">  459</span>&#160;  GPU_FAISS_ASSERT(dim1 &gt;= 0 &amp;&amp; dim2 &lt; Dim);</div>
<div class="line"><a name="l00460"></a><span class="lineno">  460</span>&#160;</div>
<div class="line"><a name="l00461"></a><span class="lineno">  461</span>&#160;  <span class="comment">// If a tensor is innermost contiguous, one cannot transpose the innermost</span></div>
<div class="line"><a name="l00462"></a><span class="lineno">  462</span>&#160;  <span class="comment">// dimension</span></div>
<div class="line"><a name="l00463"></a><span class="lineno">  463</span>&#160;  <span class="keywordflow">if</span> (InnerContig) {</div>
<div class="line"><a name="l00464"></a><span class="lineno">  464</span>&#160;    GPU_FAISS_ASSERT(dim1 != Dim - 1 &amp;&amp; dim2 != Dim - 1);</div>
<div class="line"><a name="l00465"></a><span class="lineno">  465</span>&#160;  }</div>
<div class="line"><a name="l00466"></a><span class="lineno">  466</span>&#160;</div>
<div class="line"><a name="l00467"></a><span class="lineno">  467</span>&#160;  IndexT newSize[Dim];</div>
<div class="line"><a name="l00468"></a><span class="lineno">  468</span>&#160;  IndexT newStride[Dim];</div>
<div class="line"><a name="l00469"></a><span class="lineno">  469</span>&#160;</div>
<div class="line"><a name="l00470"></a><span class="lineno">  470</span>&#160;  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; Dim; ++i) {</div>
<div class="line"><a name="l00471"></a><span class="lineno">  471</span>&#160;    newSize[i] = size_[i];</div>
<div class="line"><a name="l00472"></a><span class="lineno">  472</span>&#160;    newStride[i] = stride_[i];</div>
<div class="line"><a name="l00473"></a><span class="lineno">  473</span>&#160;  }</div>
<div class="line"><a name="l00474"></a><span class="lineno">  474</span>&#160;</div>
<div class="line"><a name="l00475"></a><span class="lineno">  475</span>&#160;  IndexT tmp = newSize[dim1];</div>
<div class="line"><a name="l00476"></a><span class="lineno">  476</span>&#160;  newSize[dim1] = newSize[dim2];</div>
<div class="line"><a name="l00477"></a><span class="lineno">  477</span>&#160;  newSize[dim2] = tmp;</div>
<div class="line"><a name="l00478"></a><span class="lineno">  478</span>&#160;</div>
<div class="line"><a name="l00479"></a><span class="lineno">  479</span>&#160;  tmp = newStride[dim1];</div>
<div class="line"><a name="l00480"></a><span class="lineno">  480</span>&#160;  newStride[dim1] = newStride[dim2];</div>
<div class="line"><a name="l00481"></a><span class="lineno">  481</span>&#160;  newStride[dim2] = tmp;</div>
<div class="line"><a name="l00482"></a><span class="lineno">  482</span>&#160;</div>
<div class="line"><a name="l00483"></a><span class="lineno">  483</span>&#160;  <span class="keywordflow">return</span> <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor&lt;T, Dim, InnerContig, IndexT, PtrTraits&gt;</a>(data_, newSize, newStride);</div>
<div class="line"><a name="l00484"></a><span class="lineno">  484</span>&#160;}</div>
<div class="line"><a name="l00485"></a><span class="lineno">  485</span>&#160;</div>
<div class="line"><a name="l00486"></a><span class="lineno">  486</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T, <span class="keywordtype">int</span> Dim, <span class="keywordtype">bool</span> InnerContig,</div>
<div class="line"><a name="l00487"></a><span class="lineno">  487</span>&#160;          <span class="keyword">typename</span> IndexT, <span class="keyword">template</span> &lt;<span class="keyword">typename</span> U&gt; <span class="keyword">class </span>PtrTraits&gt;</div>
<div class="line"><a name="l00488"></a><span class="lineno">  488</span>&#160;<span class="keyword">template</span> &lt;<span class="keywordtype">int</span> NewDim&gt;</div>
<div class="line"><a name="l00489"></a><span class="lineno">  489</span>&#160;__host__ __device__ <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor&lt;T, NewDim, InnerContig, IndexT, PtrTraits&gt;</a></div>
<div class="line"><a name="l00490"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1Tensor.html#a309eb97e9c6dbfdecf383343c072d38c">  490</a></span>&#160;<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a309eb97e9c6dbfdecf383343c072d38c">Tensor&lt;T, Dim, InnerContig, IndexT, PtrTraits&gt;::upcastOuter</a>() {</div>
<div class="line"><a name="l00491"></a><span class="lineno">  491</span>&#160;  <span class="comment">// Can only create tensors of greater dimension</span></div>
<div class="line"><a name="l00492"></a><span class="lineno">  492</span>&#160;  static_assert(NewDim &gt; Dim, <span class="stringliteral">&quot;Can only upcast to greater dim&quot;</span>);</div>
<div class="line"><a name="l00493"></a><span class="lineno">  493</span>&#160;</div>
<div class="line"><a name="l00494"></a><span class="lineno">  494</span>&#160;  IndexT newSize[NewDim];</div>
<div class="line"><a name="l00495"></a><span class="lineno">  495</span>&#160;  IndexT newStride[NewDim];</div>
<div class="line"><a name="l00496"></a><span class="lineno">  496</span>&#160;</div>
<div class="line"><a name="l00497"></a><span class="lineno">  497</span>&#160;  <span class="keywordtype">int</span> shift = NewDim - Dim;</div>
<div class="line"><a name="l00498"></a><span class="lineno">  498</span>&#160;</div>
<div class="line"><a name="l00499"></a><span class="lineno">  499</span>&#160;  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; NewDim; ++i) {</div>
<div class="line"><a name="l00500"></a><span class="lineno">  500</span>&#160;    <span class="keywordflow">if</span> (i &lt; shift) {</div>
<div class="line"><a name="l00501"></a><span class="lineno">  501</span>&#160;      <span class="comment">// These are the extended dimensions</span></div>
<div class="line"><a name="l00502"></a><span class="lineno">  502</span>&#160;      newSize[i] = (IndexT) 1;</div>
<div class="line"><a name="l00503"></a><span class="lineno">  503</span>&#160;      newStride[i] = size_[0] * stride_[0];</div>
<div class="line"><a name="l00504"></a><span class="lineno">  504</span>&#160;    } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00505"></a><span class="lineno">  505</span>&#160;      <span class="comment">// Shift the remaining dimensions</span></div>
<div class="line"><a name="l00506"></a><span class="lineno">  506</span>&#160;      newSize[i] = size_[i - shift];</div>
<div class="line"><a name="l00507"></a><span class="lineno">  507</span>&#160;      newStride[i] = stride_[i - shift];</div>
<div class="line"><a name="l00508"></a><span class="lineno">  508</span>&#160;    }</div>
<div class="line"><a name="l00509"></a><span class="lineno">  509</span>&#160;  }</div>
<div class="line"><a name="l00510"></a><span class="lineno">  510</span>&#160;</div>
<div class="line"><a name="l00511"></a><span class="lineno">  511</span>&#160;  <span class="keywordflow">return</span> <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor&lt;T, NewDim, InnerContig, IndexT, PtrTraits&gt;</a>(</div>
<div class="line"><a name="l00512"></a><span class="lineno">  512</span>&#160;    data_, newSize, newStride);</div>
<div class="line"><a name="l00513"></a><span class="lineno">  513</span>&#160;}</div>
<div class="line"><a name="l00514"></a><span class="lineno">  514</span>&#160;</div>
<div class="line"><a name="l00515"></a><span class="lineno">  515</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T, <span class="keywordtype">int</span> Dim, <span class="keywordtype">bool</span> InnerContig,</div>
<div class="line"><a name="l00516"></a><span class="lineno">  516</span>&#160;          <span class="keyword">typename</span> IndexT, <span class="keyword">template</span> &lt;<span class="keyword">typename</span> U&gt; <span class="keyword">class </span>PtrTraits&gt;</div>
<div class="line"><a name="l00517"></a><span class="lineno">  517</span>&#160;<span class="keyword">template</span> &lt;<span class="keywordtype">int</span> NewDim&gt;</div>
<div class="line"><a name="l00518"></a><span class="lineno">  518</span>&#160;__host__ __device__ <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor&lt;T, NewDim, InnerContig, IndexT, PtrTraits&gt;</a></div>
<div class="line"><a name="l00519"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1Tensor.html#aee5cf46d16344e2a055cf63adb07d24a">  519</a></span>&#160;<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#aee5cf46d16344e2a055cf63adb07d24a">Tensor&lt;T, Dim, InnerContig, IndexT, PtrTraits&gt;::upcastInner</a>() {</div>
<div class="line"><a name="l00520"></a><span class="lineno">  520</span>&#160;  <span class="comment">// Can only create tensors of greater dimension</span></div>
<div class="line"><a name="l00521"></a><span class="lineno">  521</span>&#160;  static_assert(NewDim &gt; Dim, <span class="stringliteral">&quot;Can only upcast to greater dim&quot;</span>);</div>
<div class="line"><a name="l00522"></a><span class="lineno">  522</span>&#160;</div>
<div class="line"><a name="l00523"></a><span class="lineno">  523</span>&#160;  IndexT newSize[NewDim];</div>
<div class="line"><a name="l00524"></a><span class="lineno">  524</span>&#160;  IndexT newStride[NewDim];</div>
<div class="line"><a name="l00525"></a><span class="lineno">  525</span>&#160;</div>
<div class="line"><a name="l00526"></a><span class="lineno">  526</span>&#160;  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; NewDim; ++i) {</div>
<div class="line"><a name="l00527"></a><span class="lineno">  527</span>&#160;    <span class="keywordflow">if</span> (i &lt; Dim) {</div>
<div class="line"><a name="l00528"></a><span class="lineno">  528</span>&#160;      <span class="comment">// Existing dimensions get copied over</span></div>
<div class="line"><a name="l00529"></a><span class="lineno">  529</span>&#160;      newSize[i] = size_[i];</div>
<div class="line"><a name="l00530"></a><span class="lineno">  530</span>&#160;      newStride[i] = stride_[i];</div>
<div class="line"><a name="l00531"></a><span class="lineno">  531</span>&#160;    } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00532"></a><span class="lineno">  532</span>&#160;      <span class="comment">// Extended dimensions</span></div>
<div class="line"><a name="l00533"></a><span class="lineno">  533</span>&#160;      newSize[i] = (IndexT) 1;</div>
<div class="line"><a name="l00534"></a><span class="lineno">  534</span>&#160;      newStride[i] = (IndexT) 1;</div>
<div class="line"><a name="l00535"></a><span class="lineno">  535</span>&#160;    }</div>
<div class="line"><a name="l00536"></a><span class="lineno">  536</span>&#160;  }</div>
<div class="line"><a name="l00537"></a><span class="lineno">  537</span>&#160;</div>
<div class="line"><a name="l00538"></a><span class="lineno">  538</span>&#160;  <span class="keywordflow">return</span> <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor&lt;T, NewDim, InnerContig, IndexT, PtrTraits&gt;</a>(</div>
<div class="line"><a name="l00539"></a><span class="lineno">  539</span>&#160;    data_, newSize, newStride);</div>
<div class="line"><a name="l00540"></a><span class="lineno">  540</span>&#160;}</div>
<div class="line"><a name="l00541"></a><span class="lineno">  541</span>&#160;</div>
<div class="line"><a name="l00542"></a><span class="lineno">  542</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T, <span class="keywordtype">int</span> Dim, <span class="keywordtype">bool</span> InnerContig,</div>
<div class="line"><a name="l00543"></a><span class="lineno">  543</span>&#160;          <span class="keyword">typename</span> IndexT, <span class="keyword">template</span> &lt;<span class="keyword">typename</span> U&gt; <span class="keyword">class </span>PtrTraits&gt;</div>
<div class="line"><a name="l00544"></a><span class="lineno">  544</span>&#160;<span class="keyword">template</span> &lt;<span class="keywordtype">int</span> NewDim&gt;</div>
<div class="line"><a name="l00545"></a><span class="lineno">  545</span>&#160;__host__ __device__ <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor&lt;T, NewDim, InnerContig, IndexT, PtrTraits&gt;</a></div>
<div class="line"><a name="l00546"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1Tensor.html#a2185b0c1c2c06cc3a4dab6a88eb6d001">  546</a></span>&#160;<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a2185b0c1c2c06cc3a4dab6a88eb6d001">Tensor&lt;T, Dim, InnerContig, IndexT, PtrTraits&gt;::downcastOuter</a>() {</div>
<div class="line"><a name="l00547"></a><span class="lineno">  547</span>&#160;  <span class="comment">// Can only create tensors of lesser dimension</span></div>
<div class="line"><a name="l00548"></a><span class="lineno">  548</span>&#160;  static_assert(NewDim &lt; Dim, <span class="stringliteral">&quot;Can only downcast to lesser dim&quot;</span>);</div>
<div class="line"><a name="l00549"></a><span class="lineno">  549</span>&#160;</div>
<div class="line"><a name="l00550"></a><span class="lineno">  550</span>&#160;  <span class="comment">// We can&#39;t downcast non-contiguous tensors, since it leaves</span></div>
<div class="line"><a name="l00551"></a><span class="lineno">  551</span>&#160;  <span class="comment">// garbage data in the tensor. The tensor needs to be contiguous</span></div>
<div class="line"><a name="l00552"></a><span class="lineno">  552</span>&#160;  <span class="comment">// in all of the dimensions we are collapsing (no padding in</span></div>
<div class="line"><a name="l00553"></a><span class="lineno">  553</span>&#160;  <span class="comment">// them).</span></div>
<div class="line"><a name="l00554"></a><span class="lineno">  554</span>&#160;  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; Dim - NewDim; ++i) {</div>
<div class="line"><a name="l00555"></a><span class="lineno">  555</span>&#160;    <span class="keywordtype">bool</span> cont = isContiguousDim(i);</div>
<div class="line"><a name="l00556"></a><span class="lineno">  556</span>&#160;    GPU_FAISS_ASSERT(cont);</div>
<div class="line"><a name="l00557"></a><span class="lineno">  557</span>&#160;  }</div>
<div class="line"><a name="l00558"></a><span class="lineno">  558</span>&#160;</div>
<div class="line"><a name="l00559"></a><span class="lineno">  559</span>&#160;  IndexT newSize[NewDim];</div>
<div class="line"><a name="l00560"></a><span class="lineno">  560</span>&#160;  IndexT newStride[NewDim];</div>
<div class="line"><a name="l00561"></a><span class="lineno">  561</span>&#160;</div>
<div class="line"><a name="l00562"></a><span class="lineno">  562</span>&#160;  <span class="keywordtype">int</span> ignoredDims = Dim - NewDim;</div>
<div class="line"><a name="l00563"></a><span class="lineno">  563</span>&#160;  IndexT collapsedSize = 1;</div>
<div class="line"><a name="l00564"></a><span class="lineno">  564</span>&#160;</div>
<div class="line"><a name="l00565"></a><span class="lineno">  565</span>&#160;  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; Dim; ++i) {</div>
<div class="line"><a name="l00566"></a><span class="lineno">  566</span>&#160;    <span class="keywordflow">if</span> (i &lt; ignoredDims) {</div>
<div class="line"><a name="l00567"></a><span class="lineno">  567</span>&#160;      <span class="comment">// Collapse these dimensions</span></div>
<div class="line"><a name="l00568"></a><span class="lineno">  568</span>&#160;      collapsedSize *= getSize(i);</div>
<div class="line"><a name="l00569"></a><span class="lineno">  569</span>&#160;    } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00570"></a><span class="lineno">  570</span>&#160;      <span class="comment">// Non-collapsed dimensions</span></div>
<div class="line"><a name="l00571"></a><span class="lineno">  571</span>&#160;      <span class="keywordflow">if</span> (i == ignoredDims) {</div>
<div class="line"><a name="l00572"></a><span class="lineno">  572</span>&#160;        <span class="comment">// This is the first non-collapsed dimension</span></div>
<div class="line"><a name="l00573"></a><span class="lineno">  573</span>&#160;        newSize[i - ignoredDims] = collapsedSize * getSize(i);</div>
<div class="line"><a name="l00574"></a><span class="lineno">  574</span>&#160;      } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00575"></a><span class="lineno">  575</span>&#160;        <span class="comment">// Subsequent non-collapsed dimensions</span></div>
<div class="line"><a name="l00576"></a><span class="lineno">  576</span>&#160;        newSize[i - ignoredDims] = getSize(i);</div>
<div class="line"><a name="l00577"></a><span class="lineno">  577</span>&#160;      }</div>
<div class="line"><a name="l00578"></a><span class="lineno">  578</span>&#160;</div>
<div class="line"><a name="l00579"></a><span class="lineno">  579</span>&#160;      newStride[i - ignoredDims] = getStride(i);</div>
<div class="line"><a name="l00580"></a><span class="lineno">  580</span>&#160;    }</div>
<div class="line"><a name="l00581"></a><span class="lineno">  581</span>&#160;  }</div>
<div class="line"><a name="l00582"></a><span class="lineno">  582</span>&#160;</div>
<div class="line"><a name="l00583"></a><span class="lineno">  583</span>&#160;  <span class="keywordflow">return</span> <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor&lt;T, NewDim, InnerContig, IndexT, PtrTraits&gt;</a>(</div>
<div class="line"><a name="l00584"></a><span class="lineno">  584</span>&#160;    data_, newSize, newStride);</div>
<div class="line"><a name="l00585"></a><span class="lineno">  585</span>&#160;}</div>
<div class="line"><a name="l00586"></a><span class="lineno">  586</span>&#160;</div>
<div class="line"><a name="l00587"></a><span class="lineno">  587</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T, <span class="keywordtype">int</span> Dim, <span class="keywordtype">bool</span> InnerContig,</div>
<div class="line"><a name="l00588"></a><span class="lineno">  588</span>&#160;          <span class="keyword">typename</span> IndexT, <span class="keyword">template</span> &lt;<span class="keyword">typename</span> U&gt; <span class="keyword">class </span>PtrTraits&gt;</div>
<div class="line"><a name="l00589"></a><span class="lineno">  589</span>&#160;<span class="keyword">template</span> &lt;<span class="keywordtype">int</span> NewDim&gt;</div>
<div class="line"><a name="l00590"></a><span class="lineno">  590</span>&#160;__host__ __device__ <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor&lt;T, NewDim, InnerContig, IndexT, PtrTraits&gt;</a></div>
<div class="line"><a name="l00591"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1Tensor.html#a6a43125c6f429f28161d59f19eb8e5c5">  591</a></span>&#160;<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a6a43125c6f429f28161d59f19eb8e5c5">Tensor&lt;T, Dim, InnerContig, IndexT, PtrTraits&gt;::downcastInner</a>() {</div>
<div class="line"><a name="l00592"></a><span class="lineno">  592</span>&#160;  <span class="comment">// Can only create tensors of lesser dimension</span></div>
<div class="line"><a name="l00593"></a><span class="lineno">  593</span>&#160;  static_assert(NewDim &lt; Dim, <span class="stringliteral">&quot;Can only downcast to lesser dim&quot;</span>);</div>
<div class="line"><a name="l00594"></a><span class="lineno">  594</span>&#160;</div>
<div class="line"><a name="l00595"></a><span class="lineno">  595</span>&#160;  <span class="comment">// We can&#39;t downcast non-contiguous tensors, since it leaves</span></div>
<div class="line"><a name="l00596"></a><span class="lineno">  596</span>&#160;  <span class="comment">// garbage data in the tensor. The tensor needs to be contiguous</span></div>
<div class="line"><a name="l00597"></a><span class="lineno">  597</span>&#160;  <span class="comment">// in all of the dimensions we are collapsing (no padding in</span></div>
<div class="line"><a name="l00598"></a><span class="lineno">  598</span>&#160;  <span class="comment">// them).</span></div>
<div class="line"><a name="l00599"></a><span class="lineno">  599</span>&#160;  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = NewDim; i &lt; Dim; ++i) {</div>
<div class="line"><a name="l00600"></a><span class="lineno">  600</span>&#160;    GPU_FAISS_ASSERT(isContiguousDim(i));</div>
<div class="line"><a name="l00601"></a><span class="lineno">  601</span>&#160;  }</div>
<div class="line"><a name="l00602"></a><span class="lineno">  602</span>&#160;</div>
<div class="line"><a name="l00603"></a><span class="lineno">  603</span>&#160;  IndexT newSize[NewDim];</div>
<div class="line"><a name="l00604"></a><span class="lineno">  604</span>&#160;  IndexT newStride[NewDim];</div>
<div class="line"><a name="l00605"></a><span class="lineno">  605</span>&#160;</div>
<div class="line"><a name="l00606"></a><span class="lineno">  606</span>&#160;  IndexT collapsedSize = 1;</div>
<div class="line"><a name="l00607"></a><span class="lineno">  607</span>&#160;</div>
<div class="line"><a name="l00608"></a><span class="lineno">  608</span>&#160;  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = Dim - 1; i &gt;= 0; --i) {</div>
<div class="line"><a name="l00609"></a><span class="lineno">  609</span>&#160;    <span class="keywordflow">if</span> (i &gt;= NewDim) {</div>
<div class="line"><a name="l00610"></a><span class="lineno">  610</span>&#160;      <span class="comment">// Collapse these dimensions</span></div>
<div class="line"><a name="l00611"></a><span class="lineno">  611</span>&#160;      collapsedSize *= getSize(i);</div>
<div class="line"><a name="l00612"></a><span class="lineno">  612</span>&#160;    } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00613"></a><span class="lineno">  613</span>&#160;      <span class="comment">// Non-collapsed dimensions</span></div>
<div class="line"><a name="l00614"></a><span class="lineno">  614</span>&#160;      <span class="keywordflow">if</span> (i == NewDim - 1) {</div>
<div class="line"><a name="l00615"></a><span class="lineno">  615</span>&#160;        <span class="comment">// This is the first non-collapsed dimension</span></div>
<div class="line"><a name="l00616"></a><span class="lineno">  616</span>&#160;        newSize[i] = collapsedSize * getSize(i);</div>
<div class="line"><a name="l00617"></a><span class="lineno">  617</span>&#160;        newStride[i] = getStride(Dim - 1);</div>
<div class="line"><a name="l00618"></a><span class="lineno">  618</span>&#160;      } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00619"></a><span class="lineno">  619</span>&#160;        <span class="comment">// Subsequent non-collapsed dimensions</span></div>
<div class="line"><a name="l00620"></a><span class="lineno">  620</span>&#160;        newSize[i] = getSize(i);</div>
<div class="line"><a name="l00621"></a><span class="lineno">  621</span>&#160;        newStride[i] = getStride(i);</div>
<div class="line"><a name="l00622"></a><span class="lineno">  622</span>&#160;      }</div>
<div class="line"><a name="l00623"></a><span class="lineno">  623</span>&#160;    }</div>
<div class="line"><a name="l00624"></a><span class="lineno">  624</span>&#160;  }</div>
<div class="line"><a name="l00625"></a><span class="lineno">  625</span>&#160;</div>
<div class="line"><a name="l00626"></a><span class="lineno">  626</span>&#160;  <span class="keywordflow">return</span> <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor&lt;T, NewDim, InnerContig, IndexT, PtrTraits&gt;</a>(</div>
<div class="line"><a name="l00627"></a><span class="lineno">  627</span>&#160;    data_, newSize, newStride);</div>
<div class="line"><a name="l00628"></a><span class="lineno">  628</span>&#160;}</div>
<div class="line"><a name="l00629"></a><span class="lineno">  629</span>&#160;</div>
<div class="line"><a name="l00630"></a><span class="lineno">  630</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T, <span class="keywordtype">int</span> Dim, <span class="keywordtype">bool</span> InnerContig,</div>
<div class="line"><a name="l00631"></a><span class="lineno">  631</span>&#160;          <span class="keyword">typename</span> IndexT, <span class="keyword">template</span> &lt;<span class="keyword">typename</span> U&gt; <span class="keyword">class </span>PtrTraits&gt;</div>
<div class="line"><a name="l00632"></a><span class="lineno">  632</span>&#160;<span class="keyword">template</span> &lt;<span class="keywordtype">int</span> SubDim&gt;</div>
<div class="line"><a name="l00633"></a><span class="lineno">  633</span>&#160;__host__ __device__ <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor&lt;T, SubDim, InnerContig, IndexT, PtrTraits&gt;</a></div>
<div class="line"><a name="l00634"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1Tensor.html#a74dbc09519c9c14479b2d18f2e5042e8">  634</a></span>&#160;<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a35a63cfa4034a8ee14a999132d8a1828">Tensor&lt;T, Dim, InnerContig, IndexT, PtrTraits&gt;::view</a>(DataPtrType at) {</div>
<div class="line"><a name="l00635"></a><span class="lineno">  635</span>&#160;  static_assert(SubDim &gt;= 1 &amp;&amp; SubDim &lt; Dim,</div>
<div class="line"><a name="l00636"></a><span class="lineno">  636</span>&#160;                <span class="stringliteral">&quot;can only create view of lesser dim&quot;</span>);</div>
<div class="line"><a name="l00637"></a><span class="lineno">  637</span>&#160;</div>
<div class="line"><a name="l00638"></a><span class="lineno">  638</span>&#160;  IndexT viewSizes[SubDim];</div>
<div class="line"><a name="l00639"></a><span class="lineno">  639</span>&#160;  IndexT viewStrides[SubDim];</div>
<div class="line"><a name="l00640"></a><span class="lineno">  640</span>&#160;</div>
<div class="line"><a name="l00641"></a><span class="lineno">  641</span>&#160;  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; SubDim; ++i) {</div>
<div class="line"><a name="l00642"></a><span class="lineno">  642</span>&#160;    viewSizes[i] = size_[Dim - SubDim + i];</div>
<div class="line"><a name="l00643"></a><span class="lineno">  643</span>&#160;    viewStrides[i] = stride_[Dim - SubDim + i];</div>
<div class="line"><a name="l00644"></a><span class="lineno">  644</span>&#160;  }</div>
<div class="line"><a name="l00645"></a><span class="lineno">  645</span>&#160;</div>
<div class="line"><a name="l00646"></a><span class="lineno">  646</span>&#160;  <span class="keywordflow">return</span> <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor&lt;T, SubDim, InnerContig, IndexT, PtrTraits&gt;</a>(</div>
<div class="line"><a name="l00647"></a><span class="lineno">  647</span>&#160;    at, viewSizes, viewStrides);</div>
<div class="line"><a name="l00648"></a><span class="lineno">  648</span>&#160;}</div>
<div class="line"><a name="l00649"></a><span class="lineno">  649</span>&#160;</div>
<div class="line"><a name="l00650"></a><span class="lineno">  650</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T, <span class="keywordtype">int</span> Dim, <span class="keywordtype">bool</span> InnerContig,</div>
<div class="line"><a name="l00651"></a><span class="lineno">  651</span>&#160;          <span class="keyword">typename</span> IndexT, <span class="keyword">template</span> &lt;<span class="keyword">typename</span> U&gt; <span class="keyword">class </span>PtrTraits&gt;</div>
<div class="line"><a name="l00652"></a><span class="lineno">  652</span>&#160;<span class="keyword">template</span> &lt;<span class="keywordtype">int</span> SubDim&gt;</div>
<div class="line"><a name="l00653"></a><span class="lineno">  653</span>&#160;__host__ __device__ <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor&lt;T, SubDim, InnerContig, IndexT, PtrTraits&gt;</a></div>
<div class="line"><a name="l00654"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1Tensor.html#a35a63cfa4034a8ee14a999132d8a1828">  654</a></span>&#160;<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a35a63cfa4034a8ee14a999132d8a1828">Tensor&lt;T, Dim, InnerContig, IndexT, PtrTraits&gt;::view</a>() {</div>
<div class="line"><a name="l00655"></a><span class="lineno">  655</span>&#160;  <span class="keywordflow">return</span> view&lt;SubDim&gt;(data_);</div>
<div class="line"><a name="l00656"></a><span class="lineno">  656</span>&#160;}</div>
<div class="line"><a name="l00657"></a><span class="lineno">  657</span>&#160;</div>
<div class="line"><a name="l00658"></a><span class="lineno">  658</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T, <span class="keywordtype">int</span> Dim, <span class="keywordtype">bool</span> InnerContig,</div>
<div class="line"><a name="l00659"></a><span class="lineno">  659</span>&#160;          <span class="keyword">typename</span> IndexT, <span class="keyword">template</span> &lt;<span class="keyword">typename</span> U&gt; <span class="keyword">class </span>PtrTraits&gt;</div>
<div class="line"><a name="l00660"></a><span class="lineno">  660</span>&#160;__host__ __device__ <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor&lt;T, Dim, InnerContig, IndexT, PtrTraits&gt;</a></div>
<div class="line"><a name="l00661"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1Tensor.html#ac2d0fc7199901a8e0788b58f0970b133">  661</a></span>&#160;<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#ac2d0fc7199901a8e0788b58f0970b133">Tensor&lt;T, Dim, InnerContig, IndexT, PtrTraits&gt;::narrowOutermost</a>(IndexT start,</div>
<div class="line"><a name="l00662"></a><span class="lineno">  662</span>&#160;                                                                IndexT size) {</div>
<div class="line"><a name="l00663"></a><span class="lineno">  663</span>&#160;  <span class="keywordflow">return</span> this-&gt;narrow(0, start, size);</div>
<div class="line"><a name="l00664"></a><span class="lineno">  664</span>&#160;}</div>
<div class="line"><a name="l00665"></a><span class="lineno">  665</span>&#160;</div>
<div class="line"><a name="l00666"></a><span class="lineno">  666</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T, <span class="keywordtype">int</span> Dim, <span class="keywordtype">bool</span> InnerContig,</div>
<div class="line"><a name="l00667"></a><span class="lineno">  667</span>&#160;          <span class="keyword">typename</span> IndexT, <span class="keyword">template</span> &lt;<span class="keyword">typename</span> U&gt; <span class="keyword">class </span>PtrTraits&gt;</div>
<div class="line"><a name="l00668"></a><span class="lineno">  668</span>&#160;__host__ __device__ <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor&lt;T, Dim, InnerContig, IndexT, PtrTraits&gt;</a></div>
<div class="line"><a name="l00669"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1Tensor.html#ab6db6bf86dd0f7e877af3a6ae2100fe3">  669</a></span>&#160;<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#ab6db6bf86dd0f7e877af3a6ae2100fe3">Tensor&lt;T, Dim, InnerContig, IndexT, PtrTraits&gt;::narrow</a>(<span class="keywordtype">int</span> dim,</div>
<div class="line"><a name="l00670"></a><span class="lineno">  670</span>&#160;                                                       IndexT start,</div>
<div class="line"><a name="l00671"></a><span class="lineno">  671</span>&#160;                                                       IndexT size) {</div>
<div class="line"><a name="l00672"></a><span class="lineno">  672</span>&#160;  DataPtrType newData = data_;</div>
<div class="line"><a name="l00673"></a><span class="lineno">  673</span>&#160;</div>
<div class="line"><a name="l00674"></a><span class="lineno">  674</span>&#160;  GPU_FAISS_ASSERT(start &gt;= 0 &amp;&amp;</div>
<div class="line"><a name="l00675"></a><span class="lineno">  675</span>&#160;                   start &lt; size_[dim] &amp;&amp;</div>
<div class="line"><a name="l00676"></a><span class="lineno">  676</span>&#160;                   (start + size) &lt;= size_[dim]);</div>
<div class="line"><a name="l00677"></a><span class="lineno">  677</span>&#160;</div>
<div class="line"><a name="l00678"></a><span class="lineno">  678</span>&#160;  <span class="keywordflow">if</span> (start &gt; 0) {</div>
<div class="line"><a name="l00679"></a><span class="lineno">  679</span>&#160;    newData += (size_t) start * stride_[dim];</div>
<div class="line"><a name="l00680"></a><span class="lineno">  680</span>&#160;  }</div>
<div class="line"><a name="l00681"></a><span class="lineno">  681</span>&#160;</div>
<div class="line"><a name="l00682"></a><span class="lineno">  682</span>&#160;  IndexT newSize[Dim];</div>
<div class="line"><a name="l00683"></a><span class="lineno">  683</span>&#160;  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; Dim; ++i) {</div>
<div class="line"><a name="l00684"></a><span class="lineno">  684</span>&#160;    <span class="keywordflow">if</span> (i == dim) {</div>
<div class="line"><a name="l00685"></a><span class="lineno">  685</span>&#160;      GPU_FAISS_ASSERT(start + size &lt;= size_[dim]);</div>
<div class="line"><a name="l00686"></a><span class="lineno">  686</span>&#160;      newSize[i] = size;</div>
<div class="line"><a name="l00687"></a><span class="lineno">  687</span>&#160;    } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00688"></a><span class="lineno">  688</span>&#160;      newSize[i] = size_[i];</div>
<div class="line"><a name="l00689"></a><span class="lineno">  689</span>&#160;    }</div>
<div class="line"><a name="l00690"></a><span class="lineno">  690</span>&#160;  }</div>
<div class="line"><a name="l00691"></a><span class="lineno">  691</span>&#160;</div>
<div class="line"><a name="l00692"></a><span class="lineno">  692</span>&#160;  <span class="comment">// If we were innermost contiguous before, we are still innermost contiguous</span></div>
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<div class="line"><a name="l00694"></a><span class="lineno">  694</span>&#160;}</div>
<div class="line"><a name="l00695"></a><span class="lineno">  695</span>&#160;</div>
<div class="line"><a name="l00696"></a><span class="lineno">  696</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T, <span class="keywordtype">int</span> Dim, <span class="keywordtype">bool</span> InnerContig,</div>
<div class="line"><a name="l00697"></a><span class="lineno">  697</span>&#160;          <span class="keyword">typename</span> IndexT, <span class="keyword">template</span> &lt;<span class="keyword">typename</span> U&gt; <span class="keyword">class </span>PtrTraits&gt;</div>
<div class="line"><a name="l00698"></a><span class="lineno">  698</span>&#160;<span class="keyword">template</span> &lt;<span class="keywordtype">int</span> NewDim&gt;</div>
<div class="line"><a name="l00699"></a><span class="lineno">  699</span>&#160;__host__ __device__ <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor&lt;T, NewDim, InnerContig, IndexT, PtrTraits&gt;</a></div>
<div class="line"><a name="l00700"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1Tensor.html#a665d97851f0929cad7fc76f945b64c97">  700</a></span>&#160;<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a35a63cfa4034a8ee14a999132d8a1828">Tensor&lt;T, Dim, InnerContig, IndexT, PtrTraits&gt;::view</a>(</div>
<div class="line"><a name="l00701"></a><span class="lineno">  701</span>&#160;  std::initializer_list&lt;IndexT&gt; sizes) {</div>
<div class="line"><a name="l00702"></a><span class="lineno">  702</span>&#160;  GPU_FAISS_ASSERT(this-&gt;isContiguous());</div>
<div class="line"><a name="l00703"></a><span class="lineno">  703</span>&#160;</div>
<div class="line"><a name="l00704"></a><span class="lineno">  704</span>&#160;  GPU_FAISS_ASSERT(sizes.size() == NewDim);</div>
<div class="line"><a name="l00705"></a><span class="lineno">  705</span>&#160;</div>
<div class="line"><a name="l00706"></a><span class="lineno">  706</span>&#160;  <span class="comment">// The total size of the new view must be the same as the total size</span></div>
<div class="line"><a name="l00707"></a><span class="lineno">  707</span>&#160;  <span class="comment">// of the old view</span></div>
<div class="line"><a name="l00708"></a><span class="lineno">  708</span>&#160;  <span class="keywordtype">size_t</span> curSize = numElements();</div>
<div class="line"><a name="l00709"></a><span class="lineno">  709</span>&#160;  <span class="keywordtype">size_t</span> newSize = 1;</div>
<div class="line"><a name="l00710"></a><span class="lineno">  710</span>&#160;</div>
<div class="line"><a name="l00711"></a><span class="lineno">  711</span>&#160;  <span class="keywordflow">for</span> (<span class="keyword">auto</span> s : sizes) {</div>
<div class="line"><a name="l00712"></a><span class="lineno">  712</span>&#160;    newSize *= s;</div>
<div class="line"><a name="l00713"></a><span class="lineno">  713</span>&#160;  }</div>
<div class="line"><a name="l00714"></a><span class="lineno">  714</span>&#160;</div>
<div class="line"><a name="l00715"></a><span class="lineno">  715</span>&#160;  GPU_FAISS_ASSERT(curSize == newSize);</div>
<div class="line"><a name="l00716"></a><span class="lineno">  716</span>&#160;  <span class="keywordflow">return</span> <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor&lt;T, NewDim, true, IndexT, PtrTraits&gt;</a>(data(), sizes);</div>
<div class="line"><a name="l00717"></a><span class="lineno">  717</span>&#160;}</div>
<div class="line"><a name="l00718"></a><span class="lineno">  718</span>&#160;</div>
<div class="line"><a name="l00719"></a><span class="lineno">  719</span>&#160;} } <span class="comment">// namespace</span></div>
<div class="ttc" id="classfaiss_1_1gpu_1_1Tensor_html_a309eb97e9c6dbfdecf383343c072d38c"><div class="ttname"><a href="classfaiss_1_1gpu_1_1Tensor.html#a309eb97e9c6dbfdecf383343c072d38c">faiss::gpu::Tensor::upcastOuter</a></div><div class="ttdeci">__host__ __device__ Tensor&lt; T, NewDim, InnerContig, IndexT, PtrTraits &gt; upcastOuter()</div><div class="ttdef"><b>Definition:</b> <a href="Tensor-inl_8cuh_source.html#l00490">Tensor-inl.cuh:490</a></div></div>
<div class="ttc" id="classfaiss_1_1gpu_1_1Tensor_html_a9f0c817e9751fe02926c2346a97f0350"><div class="ttname"><a href="classfaiss_1_1gpu_1_1Tensor.html#a9f0c817e9751fe02926c2346a97f0350">faiss::gpu::Tensor::castIndexType</a></div><div class="ttdeci">__host__ Tensor&lt; T, Dim, InnerContig, NewIndexT, PtrTraits &gt; castIndexType() const </div><div class="ttdef"><b>Definition:</b> <a href="Tensor-inl_8cuh_source.html#l00341">Tensor-inl.cuh:341</a></div></div>
<div class="ttc" id="classfaiss_1_1gpu_1_1Tensor_html_a3f4e3c6afdf4a03308756b6ae6462c38"><div class="ttname"><a href="classfaiss_1_1gpu_1_1Tensor.html#a3f4e3c6afdf4a03308756b6ae6462c38">faiss::gpu::Tensor::isContiguousDim</a></div><div class="ttdeci">__host__ __device__ bool isContiguousDim(int i) const </div><div class="ttdoc">Returns true if the given dimension index has no padding. </div><div class="ttdef"><b>Definition:</b> <a href="Tensor-inl_8cuh_source.html#l00447">Tensor-inl.cuh:447</a></div></div>
<div class="ttc" id="classfaiss_1_1gpu_1_1Tensor_html_a2894f8fdfab8ec3245364a6f9e8a5259"><div class="ttname"><a href="classfaiss_1_1gpu_1_1Tensor.html#a2894f8fdfab8ec3245364a6f9e8a5259">faiss::gpu::Tensor::cast</a></div><div class="ttdeci">__host__ __device__ Tensor&lt; U, Dim, InnerContig, IndexT, PtrTraits &gt; cast()</div><div class="ttdef"><b>Definition:</b> <a href="Tensor-inl_8cuh_source.html#l00253">Tensor-inl.cuh:253</a></div></div>
<div class="ttc" id="classfaiss_1_1gpu_1_1Tensor_html_a0ba9ab7c1676b7a41a6e6b2e5a490d2f"><div class="ttname"><a href="classfaiss_1_1gpu_1_1Tensor.html#a0ba9ab7c1676b7a41a6e6b2e5a490d2f">faiss::gpu::Tensor::numElements</a></div><div class="ttdeci">__host__ __device__ size_t numElements() const </div><div class="ttdef"><b>Definition:</b> <a href="Tensor-inl_8cuh_source.html#l00388">Tensor-inl.cuh:388</a></div></div>
<div class="ttc" id="classfaiss_1_1gpu_1_1Tensor_html_a2185b0c1c2c06cc3a4dab6a88eb6d001"><div class="ttname"><a href="classfaiss_1_1gpu_1_1Tensor.html#a2185b0c1c2c06cc3a4dab6a88eb6d001">faiss::gpu::Tensor::downcastOuter</a></div><div class="ttdeci">__host__ __device__ Tensor&lt; T, NewDim, InnerContig, IndexT, PtrTraits &gt; downcastOuter()</div><div class="ttdef"><b>Definition:</b> <a href="Tensor-inl_8cuh_source.html#l00546">Tensor-inl.cuh:546</a></div></div>
<div class="ttc" id="classfaiss_1_1gpu_1_1Tensor_html_a7fbbf51f8ef6bea9cc863a86e20d994e"><div class="ttname"><a href="classfaiss_1_1gpu_1_1Tensor.html#a7fbbf51f8ef6bea9cc863a86e20d994e">faiss::gpu::Tensor::canCastResize</a></div><div class="ttdeci">__host__ __device__ bool canCastResize() const </div><div class="ttdoc">Returns true if we can castResize() this tensor to the new type. </div><div class="ttdef"><b>Definition:</b> <a href="Tensor-inl_8cuh_source.html#l00309">Tensor-inl.cuh:309</a></div></div>
<div class="ttc" id="classfaiss_1_1gpu_1_1Tensor_html_a2ec506a25e46cf7001060a6ba5ae3b94"><div class="ttname"><a href="classfaiss_1_1gpu_1_1Tensor.html#a2ec506a25e46cf7001060a6ba5ae3b94">faiss::gpu::Tensor::data_</a></div><div class="ttdeci">DataPtrType data_</div><div class="ttdoc">Raw pointer to where the tensor data begins. </div><div class="ttdef"><b>Definition:</b> <a href="Tensor_8cuh_source.html#l00344">Tensor.cuh:344</a></div></div>
<div class="ttc" id="classfaiss_1_1gpu_1_1Tensor_html_a8ae7b3f95991125a5648c3b78afd40bd"><div class="ttname"><a href="classfaiss_1_1gpu_1_1Tensor.html#a8ae7b3f95991125a5648c3b78afd40bd">faiss::gpu::Tensor::Tensor</a></div><div class="ttdeci">__host__ __device__ Tensor()</div><div class="ttdoc">Default constructor. </div><div class="ttdef"><b>Definition:</b> <a href="Tensor-inl_8cuh_source.html#l00020">Tensor-inl.cuh:20</a></div></div>
<div class="ttc" id="classfaiss_1_1gpu_1_1Tensor_html_aee5cf46d16344e2a055cf63adb07d24a"><div class="ttname"><a href="classfaiss_1_1gpu_1_1Tensor.html#aee5cf46d16344e2a055cf63adb07d24a">faiss::gpu::Tensor::upcastInner</a></div><div class="ttdeci">__host__ __device__ Tensor&lt; T, NewDim, InnerContig, IndexT, PtrTraits &gt; upcastInner()</div><div class="ttdef"><b>Definition:</b> <a href="Tensor-inl_8cuh_source.html#l00519">Tensor-inl.cuh:519</a></div></div>
<div class="ttc" id="classfaiss_1_1gpu_1_1Tensor_html_ac2d0fc7199901a8e0788b58f0970b133"><div class="ttname"><a href="classfaiss_1_1gpu_1_1Tensor.html#ac2d0fc7199901a8e0788b58f0970b133">faiss::gpu::Tensor::narrowOutermost</a></div><div class="ttdeci">__host__ __device__ Tensor&lt; T, Dim, InnerContig, IndexT, PtrTraits &gt; narrowOutermost(IndexT start, IndexT size)</div><div class="ttdef"><b>Definition:</b> <a href="Tensor-inl_8cuh_source.html#l00661">Tensor-inl.cuh:661</a></div></div>
<div class="ttc" id="classfaiss_1_1gpu_1_1Tensor_html_af4b8fe4b632cdca51ee7972ed93fc3fa"><div class="ttname"><a href="classfaiss_1_1gpu_1_1Tensor.html#af4b8fe4b632cdca51ee7972ed93fc3fa">faiss::gpu::Tensor::stride_</a></div><div class="ttdeci">IndexT stride_[Dim]</div><div class="ttdoc">Array of strides (in sizeof(T) terms) per each dimension. </div><div class="ttdef"><b>Definition:</b> <a href="Tensor_8cuh_source.html#l00347">Tensor.cuh:347</a></div></div>
<div class="ttc" id="classfaiss_1_1gpu_1_1Tensor_html_a09019c54911db891c9321fd3b34509c2"><div class="ttname"><a href="classfaiss_1_1gpu_1_1Tensor.html#a09019c54911db891c9321fd3b34509c2">faiss::gpu::Tensor::isContiguous</a></div><div class="ttdeci">__host__ __device__ bool isContiguous() const </div><div class="ttdef"><b>Definition:</b> <a href="Tensor-inl_8cuh_source.html#l00401">Tensor-inl.cuh:401</a></div></div>
<div class="ttc" id="classfaiss_1_1gpu_1_1Tensor_html_abc0ecc4f882ee09632b5a06be0619adb"><div class="ttname"><a href="classfaiss_1_1gpu_1_1Tensor.html#abc0ecc4f882ee09632b5a06be0619adb">faiss::gpu::Tensor::sizes</a></div><div class="ttdeci">__host__ __device__ const IndexT * sizes() const </div><div class="ttdoc">Returns the size array. </div><div class="ttdef"><b>Definition:</b> <a href="Tensor_8cuh_source.html#l00245">Tensor.cuh:245</a></div></div>
<div class="ttc" id="classfaiss_1_1gpu_1_1Tensor_html_a6dc00c182a92389b74c89ba7fcab40d3"><div class="ttname"><a href="classfaiss_1_1gpu_1_1Tensor.html#a6dc00c182a92389b74c89ba7fcab40d3">faiss::gpu::Tensor::copyFrom</a></div><div class="ttdeci">__host__ void copyFrom(Tensor&lt; T, Dim, InnerContig, IndexT, PtrTraits &gt; &amp;t, cudaStream_t stream)</div><div class="ttdoc">Copies a tensor into ourselves; sizes must match. </div><div class="ttdef"><b>Definition:</b> <a href="Tensor-inl_8cuh_source.html#l00132">Tensor-inl.cuh:132</a></div></div>
<div class="ttc" id="classfaiss_1_1gpu_1_1Tensor_html_ad96fbf0f5e7c06a1031b8b18f7fc01d7"><div class="ttname"><a href="classfaiss_1_1gpu_1_1Tensor.html#ad96fbf0f5e7c06a1031b8b18f7fc01d7">faiss::gpu::Tensor::size_</a></div><div class="ttdeci">IndexT size_[Dim]</div><div class="ttdoc">Size per each dimension. </div><div class="ttdef"><b>Definition:</b> <a href="Tensor_8cuh_source.html#l00350">Tensor.cuh:350</a></div></div>
<div class="ttc" id="classfaiss_1_1gpu_1_1Tensor_html_a0d831a352531281e06250cc6fe52a38a"><div class="ttname"><a href="classfaiss_1_1gpu_1_1Tensor.html#a0d831a352531281e06250cc6fe52a38a">faiss::gpu::Tensor::operator=</a></div><div class="ttdeci">__host__ __device__ Tensor&lt; T, Dim, InnerContig, IndexT, PtrTraits &gt; &amp; operator=(Tensor&lt; T, Dim, InnerContig, IndexT, PtrTraits &gt; &amp;t)</div><div class="ttdoc">Assignment. </div><div class="ttdef"><b>Definition:</b> <a href="Tensor-inl_8cuh_source.html#l00050">Tensor-inl.cuh:50</a></div></div>
<div class="ttc" id="classfaiss_1_1gpu_1_1Tensor_html_a87a777247486756e99060547a3cc833a"><div class="ttname"><a href="classfaiss_1_1gpu_1_1Tensor.html#a87a777247486756e99060547a3cc833a">faiss::gpu::Tensor::strides</a></div><div class="ttdeci">__host__ __device__ const IndexT * strides() const </div><div class="ttdoc">Returns the stride array. </div><div class="ttdef"><b>Definition:</b> <a href="Tensor_8cuh_source.html#l00250">Tensor.cuh:250</a></div></div>
<div class="ttc" id="classfaiss_1_1gpu_1_1Tensor_html_a6699c311648457f257afa340c61f417c"><div class="ttname"><a href="classfaiss_1_1gpu_1_1Tensor.html#a6699c311648457f257afa340c61f417c">faiss::gpu::Tensor::getSize</a></div><div class="ttdeci">__host__ __device__ IndexT getSize(int i) const </div><div class="ttdef"><b>Definition:</b> <a href="Tensor_8cuh_source.html#l00224">Tensor.cuh:224</a></div></div>
<div class="ttc" id="classfaiss_1_1gpu_1_1Tensor_html_a22c1e45f81f7f9e5427e2eed19f9cd11"><div class="ttname"><a href="classfaiss_1_1gpu_1_1Tensor.html#a22c1e45f81f7f9e5427e2eed19f9cd11">faiss::gpu::Tensor::isSameSize</a></div><div class="ttdeci">__host__ __device__ bool isSameSize(const Tensor&lt; OtherT, OtherDim, InnerContig, IndexT, PtrTraits &gt; &amp;rhs) const </div><div class="ttdoc">Returns true if the two tensors are of the same dimensionality and size. </div><div class="ttdef"><b>Definition:</b> <a href="Tensor-inl_8cuh_source.html#l00234">Tensor-inl.cuh:234</a></div></div>
<div class="ttc" id="classfaiss_1_1gpu_1_1Tensor_html_a6a43125c6f429f28161d59f19eb8e5c5"><div class="ttname"><a href="classfaiss_1_1gpu_1_1Tensor.html#a6a43125c6f429f28161d59f19eb8e5c5">faiss::gpu::Tensor::downcastInner</a></div><div class="ttdeci">__host__ __device__ Tensor&lt; T, NewDim, InnerContig, IndexT, PtrTraits &gt; downcastInner()</div><div class="ttdef"><b>Definition:</b> <a href="Tensor-inl_8cuh_source.html#l00591">Tensor-inl.cuh:591</a></div></div>
<div class="ttc" id="classfaiss_1_1gpu_1_1Tensor_html_ab6db6bf86dd0f7e877af3a6ae2100fe3"><div class="ttname"><a href="classfaiss_1_1gpu_1_1Tensor.html#ab6db6bf86dd0f7e877af3a6ae2100fe3">faiss::gpu::Tensor::narrow</a></div><div class="ttdeci">__host__ __device__ Tensor&lt; T, Dim, InnerContig, IndexT, PtrTraits &gt; narrow(int dim, IndexT start, IndexT size)</div><div class="ttdef"><b>Definition:</b> <a href="Tensor-inl_8cuh_source.html#l00669">Tensor-inl.cuh:669</a></div></div>
<div class="ttc" id="classfaiss_1_1gpu_1_1Tensor_html_a50411ce4d0fa32ef715e3321b6e33212"><div class="ttname"><a href="classfaiss_1_1gpu_1_1Tensor.html#a50411ce4d0fa32ef715e3321b6e33212">faiss::gpu::Tensor::data</a></div><div class="ttdeci">__host__ __device__ DataPtrType data()</div><div class="ttdoc">Returns a raw pointer to the start of our data. </div><div class="ttdef"><b>Definition:</b> <a href="Tensor_8cuh_source.html#l00176">Tensor.cuh:176</a></div></div>
<div class="ttc" id="classfaiss_1_1gpu_1_1Tensor_html_a6cc21376070a03d77661d6e333972c6a"><div class="ttname"><a href="classfaiss_1_1gpu_1_1Tensor.html#a6cc21376070a03d77661d6e333972c6a">faiss::gpu::Tensor::copyTo</a></div><div class="ttdeci">__host__ void copyTo(Tensor&lt; T, Dim, InnerContig, IndexT, PtrTraits &gt; &amp;t, cudaStream_t stream)</div><div class="ttdoc">Copies ourselves into a tensor; sizes must match. </div><div class="ttdef"><b>Definition:</b> <a href="Tensor-inl_8cuh_source.html#l00171">Tensor-inl.cuh:171</a></div></div>
<div class="ttc" id="classfaiss_1_1gpu_1_1Tensor_html"><div class="ttname"><a href="classfaiss_1_1gpu_1_1Tensor.html">faiss::gpu::Tensor</a></div><div class="ttdoc">Our tensor type. </div><div class="ttdef"><b>Definition:</b> <a href="Tensor_8cuh_source.html#l00030">Tensor.cuh:30</a></div></div>
<div class="ttc" id="classfaiss_1_1gpu_1_1Tensor_html_a2ac9dc9fa8d81f2651a1be486c14ba62"><div class="ttname"><a href="classfaiss_1_1gpu_1_1Tensor.html#a2ac9dc9fa8d81f2651a1be486c14ba62">faiss::gpu::Tensor::canUseIndexType</a></div><div class="ttdeci">__host__ bool canUseIndexType() const </div><div class="ttdef"><b>Definition:</b> <a href="Tensor-inl_8cuh_source.html#l00361">Tensor-inl.cuh:361</a></div></div>
<div class="ttc" id="classfaiss_1_1gpu_1_1Tensor_html_a82a3484a6458e3e95bb91d320f2c6731"><div class="ttname"><a href="classfaiss_1_1gpu_1_1Tensor.html#a82a3484a6458e3e95bb91d320f2c6731">faiss::gpu::Tensor::transpose</a></div><div class="ttdeci">__host__ __device__ Tensor&lt; T, Dim, InnerContig, IndexT, PtrTraits &gt; transpose(int dim1, int dim2) const </div><div class="ttdef"><b>Definition:</b> <a href="Tensor-inl_8cuh_source.html#l00456">Tensor-inl.cuh:456</a></div></div>
<div class="ttc" id="classfaiss_1_1gpu_1_1Tensor_html_a0b8bba630f7a1fa217f90b20d298420a"><div class="ttname"><a href="classfaiss_1_1gpu_1_1Tensor.html#a0b8bba630f7a1fa217f90b20d298420a">faiss::gpu::Tensor::getStride</a></div><div class="ttdeci">__host__ __device__ IndexT getStride(int i) const </div><div class="ttdef"><b>Definition:</b> <a href="Tensor_8cuh_source.html#l00230">Tensor.cuh:230</a></div></div>
<div class="ttc" id="classfaiss_1_1gpu_1_1Tensor_html_a6c9640c365134ccc33cdb2695b016eb3"><div class="ttname"><a href="classfaiss_1_1gpu_1_1Tensor.html#a6c9640c365134ccc33cdb2695b016eb3">faiss::gpu::Tensor::castResize</a></div><div class="ttdeci">__host__ __device__ Tensor&lt; U, Dim, InnerContig, IndexT, PtrTraits &gt; castResize()</div><div class="ttdef"><b>Definition:</b> <a href="Tensor-inl_8cuh_source.html#l00275">Tensor-inl.cuh:275</a></div></div>
<div class="ttc" id="classfaiss_1_1gpu_1_1Tensor_html_a35a63cfa4034a8ee14a999132d8a1828"><div class="ttname"><a href="classfaiss_1_1gpu_1_1Tensor.html#a35a63cfa4034a8ee14a999132d8a1828">faiss::gpu::Tensor::view</a></div><div class="ttdeci">__host__ __device__ Tensor&lt; T, SubDim, InnerContig, IndexT, PtrTraits &gt; view()</div><div class="ttdef"><b>Definition:</b> <a href="Tensor-inl_8cuh_source.html#l00654">Tensor-inl.cuh:654</a></div></div>
<div class="ttc" id="classfaiss_1_1gpu_1_1Tensor_html_a3067941f8f8f09fc73e2f06243699825"><div class="ttname"><a href="classfaiss_1_1gpu_1_1Tensor.html#a3067941f8f8f09fc73e2f06243699825">faiss::gpu::Tensor::isSame</a></div><div class="ttdeci">__host__ __device__ bool isSame(const Tensor&lt; OtherT, OtherDim, InnerContig, IndexT, PtrTraits &gt; &amp;rhs) const </div><div class="ttdef"><b>Definition:</b> <a href="Tensor-inl_8cuh_source.html#l00211">Tensor-inl.cuh:211</a></div></div>
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